47,110 Data jobs in the United Kingdom

Senior Data Management Professional - Data Science - Data Management Lab





Location





London





Business Area





Data





Ref #










**Description & Requirements**



Bloomberg runs on data, and in the Data department we're responsible for acquiring, interpreting and supplying data insights to our clients. Our Data teams work to collect, analyse, process, and publish the data which is the backbone of our iconic Bloomberg Terminal -- the data which ultimately moves the financial markets! Weu2019re responsible for delivering this data, news, and analytics through innovative technology -- quickly and accurately.



The Data Management Lab (DML) sits within the Data organization, supporting Datau2019s pursuit of data management excellence by aligning industry best practices with Bloomberg's established expertise in financial market data. DML empowers our data professionals to make their products u201cready-to-useu201d by promoting increased data discoverability, accessibility, appraisability, interoperability, and analysis-readiness.



As a Data Management Professional, you will play a pivotal role in ensuring the delivery of high-quality data to our clients while driving impactful business decisions. You will be an integral member of a collaborative set of teams, Quality Methods & Insights under DML that includes Data Quality, Business Intelligence and Process Engineering serving as a centre of excellence for the rest of the teams in the Data organisation. A key aspect of this role involves leading initiatives to appraise and enhance the quality of our datasets, partnering closely with Data product and Engineering teams to champion effective solutions. Simultaneously, you will leverage your analytical expertise to support the development of scalable methods and tools for analysing product, process, and people data. The analytical insights will directly support data-driven decision-making aimed at achieving quality enhancements and process optimisation across the organization. You will also contribute to the ongoing refinement of data management best practices.



**As a valued member of our team, weu2019ll trust you to:**


Lead global initiatives focused on data science applications within the realms of data quality, data product development, and operational efficiency
Design and run studies to uncover root causes of data quality issues, using techniques such as hypothesis testing, clustering, and regression analysis
Develop statistical models to detect data anomalies, predict quality issues, and optimize data manufacturing pipelines by leveraging appropriate methodologies
Deliver actionable insights through advanced analytics, and compelling data storytelling to support business decision making and innovation
Collaborate with data stakeholders and engineering partner to translate high-impact questions into scalable data science solutions
Build statistical and analytical capabilities within the team; mentor others in applying best practices in modelling and experimentation



**Youu2019ll need to have a strong combination of the following:**



_*Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role._


A PhD or Master's degree in Data Science, Economics, Statistics or a related quantitative field
3+ years' experience designing research studies as well as performing analysis such as data profiling, predictive modelling, and causal analysis
Strong coding skills ideally in Python and experience with SQL for data querying
Familiarity with version control systems (e.g., Git) and a collaborative development workflow (e.g., GitHub, GitLab)
Experience working in a data quality, data governance, or data management environment is a major plus (knowledge of DAMA, DCAM, etc. is welcome)
Excellent project management skills and the ability to communicate complex findings clearly to both technical and non-technical audiences
Knowledge of financial markets and Bloomberg products is a plus



**Does this sound like you?**



Apply if you think we're a good match. We'll get in touch to let you know what the next steps are.

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email

Senior Data Management Professional - Data Science - Data Management Lab
Location
London
Business Area
Data
Ref #

**Description & Requirements**
Bloomberg runs on data, and in the Data department we're responsible for acquiring, interpreting and supplying data insights to our clients. Our Data teams work to collect, analyse, process, and publish the data which is the backbone of our iconic Bloomberg Terminal -- the data which ultimately moves the financial markets! We're responsible for delivering this data, news, and analytics through innovative technology -- quickly and accurately.
The Data Management Lab (DML) sits within the Data organization, supporting Data's pursuit of data management excellence by aligning industry best practices with Bloomberg's established expertise in financial market data. DML empowers our data professionals to make their products "ready-to-use" by promoting increased data discoverability, accessibility, appraisability, interoperability, and analysis-readiness.
As a Data Management Professional, you will play a pivotal role in ensuring the delivery of high-quality data to our clients while driving impactful business decisions. You will be an integral member of a collaborative set of teams, Quality Methods & Insights under DML that includes Data Quality, Business Intelligence and Process Engineering serving as a centre of excellence for the rest of the teams in the Data organisation. A key aspect of this role involves leading initiatives to appraise and enhance the quality of our datasets, partnering closely with Data product and Engineering teams to champion effective solutions. Simultaneously, you will leverage your analytical expertise to support the development of scalable methods and tools for analysing product, process, and people data. The analytical insights will directly support data-driven decision-making aimed at achieving quality enhancements and process optimisation across the organization. You will also contribute to the ongoing refinement of data management best practices.
**As a valued member of our team, we'll trust you to:**
+ Lead global initiatives focused on data science applications within the realms of data quality, data product development, and operational efficiency
+ Design and run studies to uncover root causes of data quality issues, using techniques such as hypothesis testing, clustering, and regression analysis
+ Develop statistical models to detect data anomalies, predict quality issues, and optimize data manufacturing pipelines by leveraging appropriate methodologies
+ Deliver actionable insights through advanced analytics, and compelling data storytelling to support business decision making and innovation
+ Collaborate with data stakeholders and engineering partner to translate high-impact questions into scalable data science solutions
+ Build statistical and analytical capabilities within the team; mentor others in applying best practices in modelling and experimentation
**You'll need to have a strong combination of the following:**
_*Please note we use years of experience as a guide but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role._
+ A PhD or Master's degree in Data Science, Economics, Statistics or a related quantitative field
+ 3+ years' experience designing research studies as well as performing analysis such as data profiling, predictive modelling, and causal analysis
+ Strong coding skills ideally in Python and experience with SQL for data querying
+ Familiarity with version control systems (e.g., Git) and a collaborative development workflow (e.g., GitHub, GitLab)
+ Experience working in a data quality, data governance, or data management environment is a major plus (knowledge of DAMA, DCAM, etc. is welcome)
+ Excellent project management skills and the ability to communicate complex findings clearly to both technical and non-technical audiences
+ Knowledge of financial markets and Bloomberg products is a plus
**Does this sound like you?**
Apply if you think we're a good match. We'll get in touch to let you know what the next steps are.
Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email

Our client, a prominent entity in the global mining industry, is seeking a skilled Remote Geospatial Data Analyst to join their operations. This is a fully remote position, offering the flexibility to work from anywhere in the UK. You will be instrumental in processing, analyzing, and visualizing vast amounts of geospatial data to support exploration, resource estimation, and mine planning activities. Your role will involve utilizing advanced GIS software and analytical techniques to identify geological trends, delineate mineralized zones, and create detailed maps and reports. This position requires a deep understanding of geological principles, proficiency in data analysis tools, and a commitment to delivering high-quality, actionable insights.

Key responsibilities:

• Process and analyze diverse geospatial datasets (satellite imagery, aerial photography, LiDAR, geological surveys).
• Develop and implement spatial models for resource exploration and assessment.
• Create high-quality maps, reports, and visualizations for geological interpretation.
• Collaborate remotely with geologists, exploration managers, and mine engineers.
• Ensure data accuracy, integrity, and compliance with industry standards.
• Utilize programming languages (e.g., Python) for data automation and analysis.
• Stay updated on the latest advancements in GIS technology and mining geosciences.

The ideal candidate will hold a Bachelor's or Master's degree in Geology, Geosciences, Geography, or a related field, with a strong emphasis on GIS and data analysis. Proven experience (minimum 3 years) in applying geospatial techniques within the mining or exploration sector is essential. Proficiency in software such as ArcGIS, QGIS, and relevant data analysis tools (e.g., R, Python) is required. Excellent communication skills and the ability to work independently and manage time effectively in a remote setting are crucial for success in this role. This is a unique opportunity to contribute to significant mining projects from the comfort of your own home.

Our client, a global leader in the mining sector, is seeking a skilled Remote Data Analyst to support their operational efficiency from anywhere. This is a fully remote position, offering the flexibility to work from home while contributing vital insights to our mining operations. You will be responsible for collecting, processing, and analysing large datasets related to mining activities, including production, equipment performance, safety, and environmental impact. Your insights will help drive data-informed decision-making to optimise processes, improve resource allocation, and enhance overall operational outcomes.

Key responsibilities include developing and maintaining data pipelines, performing statistical analysis, creating insightful reports and dashboards using visualisation tools (e.g., Tableau, Power BI), and identifying trends and anomalies. You will collaborate closely with on-site operations teams, geologists, and engineers to understand their data needs and provide actionable recommendations. The ideal candidate will possess a strong quantitative background, with a degree in a relevant field such as Statistics, Data Science, Engineering, or a related discipline. Proven experience in data analysis, preferably within the mining, resources, or a similar industrial sector, is highly advantageous.

Proficiency in SQL, Python or R for data manipulation and analysis, and experience with data visualisation tools are essential. You should have excellent analytical, problem-solving, and communication skills, with the ability to present complex data in a clear and concise manner. Familiarity with mining-specific software or datasets is a plus. This role demands self-discipline, strong organisational skills, and the ability to work independently while meeting project deadlines. If you are a data-driven professional passionate about leveraging analytics to improve operational performance in a critical industry, we encourage you to apply for this remote opportunity.

Our client, a global leader in the mining sector, is seeking a skilled Data Scientist to join their innovative team on a fully remote basis. This is an exceptional opportunity to leverage advanced analytics and machine learning techniques to optimize mining operations, enhance safety, and drive efficiency across international sites. You will work with vast datasets to uncover actionable insights and shape critical business decisions.

As a Data Scientist, you will be responsible for the end-to-end process of data analysis, from data acquisition and cleaning to model development and deployment. You will collaborate closely with operational teams, geologists, and engineers to identify key challenges and opportunities where data-driven solutions can make a significant impact. This role requires a strong understanding of statistical modeling, machine learning algorithms, and data visualization tools.

Key Responsibilities:

• Develop and implement predictive models to forecast equipment performance, operational efficiency, and resource extraction.
• Analyze large and complex datasets from various sources (e.g., sensor data, geological surveys, operational logs) to identify patterns and trends.
• Design and build machine learning pipelines for tasks such as anomaly detection, process optimization, and risk assessment.
• Create compelling data visualizations and reports to communicate findings to both technical and non-technical stakeholders.
• Collaborate with subject matter experts to define key performance indicators (KPIs) and data requirements.
• Implement and deploy models into production environments, monitoring their performance and iterating as needed.
• Stay current with the latest advancements in data science, machine learning, and big data technologies.
• Contribute to the development of data strategy and best practices within the organization.
• Ensure data integrity, quality, and security throughout all analytical processes.

The ideal candidate will hold a Master's or Ph.D. in Data Science, Statistics, Computer Science, or a related quantitative field, with at least 4 years of professional experience as a Data Scientist. Proven expertise in Python or R, along with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch, is essential. Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure) is highly desirable. Excellent communication and problem-solving skills, coupled with the ability to work autonomously in a fully remote setting, are crucial for this role.

Our client, a global leader in the mining industry, is looking for a highly skilled and motivated Remote Data Scientist specializing in Mining Analytics. This fully remote position offers the opportunity to leverage vast datasets to drive operational efficiency, improve safety, and optimize resource extraction across diverse mining operations worldwide. The successful candidate will play a key role in developing advanced analytical models, implementing machine learning solutions, and translating complex data into actionable insights for strategic decision-making.

Key Responsibilities:

• Develop and implement advanced statistical and machine learning models to analyze mining data, including geological, operational, and financial information.
• Identify patterns, trends, and anomalies in large datasets to uncover insights related to ore grade, production efficiency, equipment performance, and safety.
• Design and build data pipelines for data ingestion, cleaning, transformation, and feature engineering specifically for mining applications.
• Collaborate with geologists, engineers, and operational managers to understand their challenges and translate them into data science problems.
• Develop predictive models for equipment failure, resource estimation, and production forecasting.
• Create interactive dashboards and visualizations to communicate complex findings to technical and non-technical stakeholders.
• Stay abreast of the latest advancements in data science, machine learning, and their applications in the mining sector.
• Ensure data quality, integrity, and security across all analytical processes.
• Contribute to the strategic roadmap for data analytics within the mining operations.
• Mentor junior data analysts and scientists.

Qualifications:

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Mining Engineering, or a related quantitative field.
• Proven experience (minimum 5 years) as a Data Scientist with a strong focus on applying advanced analytics and machine learning techniques.
• Demonstrated experience in the mining or natural resources sector, with a deep understanding of mining processes and data types.
• Proficiency in programming languages such as Python or R, and associated data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Experience with database technologies (SQL, NoSQL) and big data platforms (e.g., Spark).
• Strong knowledge of statistical modeling, machine learning algorithms, and data mining techniques.
• Excellent data visualization skills (e.g., Tableau, Power BI, Matplotlib).
• Exceptional problem-solving abilities and a curious, analytical mindset.
• Strong communication and interpersonal skills, with the ability to explain technical concepts clearly.
• Ability to work independently and manage projects effectively in a remote setting.

This fully remote role offers a highly competitive salary, comprehensive benefits, and the opportunity to make a significant impact on global mining operations. Join a forward-thinking company at the forefront of technological innovation in the industry.

We are seeking an enthusiastic and detail-oriented Junior Mining Data Analyst to join our team in Brighton, East Sussex, UK . This is an excellent opportunity for someone looking to gain hands-on experience in the mining sector, analyzing vast datasets to support operational efficiency and strategic decision-making. Your primary responsibilities will include collecting, cleaning, and processing mining-related data from various sources, such as production logs, geological surveys, and equipment sensor data. You will assist in developing and maintaining databases and data warehouses. A key part of your role will be to perform statistical analysis, identify trends, and create visualizations and reports that communicate key insights to the management team. You will work with tools like SQL, Python (with libraries such as Pandas, NumPy, Matplotlib), and business intelligence software (e.g., Tableau, Power BI) to extract and present data. The ideal candidate will have a strong analytical mindset, excellent problem-solving skills, and a keen eye for detail. While prior experience in the mining industry is not strictly required, a demonstrated interest in mining operations or natural resources is a plus. You should be comfortable working with large datasets and have a solid understanding of statistical principles. This is a hybrid role, requiring you to spend a few days a week in our Brighton office for collaborative work and meetings, with the flexibility to work remotely for the remaining days. A Bachelor's degree in Data Science, Statistics, Mining Engineering, Computer Science, or a related quantitative field is required. Proficiency in data manipulation and visualization tools is essential. Strong communication skills are needed to present findings effectively. This internship offers valuable exposure to the complexities of the mining industry and the application of data analytics in a practical setting. If you are eager to learn, contribute to meaningful projects, and kickstart your career in data analysis within the mining sector, we encourage you to apply.

Senior Data Management Professional - Data Quality - Data AI





Location





London





Business Area





Data





Ref #










**Description & Requirements**



Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock u2013 from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes - all while providing customer support to our clients.



**Our Team:**



Data AI contributes to the building of Bloombergu2019s AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. We encourage our internal processes to take advantage of new AI technologies and strengthen Datau2019s role in providing robust domain expertise and influential data artifacts to Bloombergu2019s products. This way, our clients will continue to have high quality data and access to new types of datasets.



**What's the Role?**



A Senior Data Management Professional (DMP) is a key role within our organization responsible for providing domain expertise in both financial concepts and annotation program management, to the development of our AI products. These individuals act as proactive technical leaders by setting the framework in achieving quality and consistency in the evaluation and training datasets for models that power our AI-enhanced products, and delivering scalable governance in annotation program management across Bloomberg Data. Beyond governing data processes and being problem solvers, they are expected to transform the responsibilities of the team and scale the impact beyond what's possible today.



The role in the Data AI Annotation team covers all annotation program components in developing the evaluation and training of AI models at Bloomberg. Being responsible for the quality of the annotated data, and product quality will be a crucial part of the role, with key work spanning ownership around consensus management, adjudication, and instruction and task design. The team is a critical partner in ensuring the stability and growth of the company which relies on bringing new technology to customers with increased interests in Artificial Intelligence.



**Weu2019ll trust you to:**


Create strategies to analyze processes and data quality questions to ensure our datasets are fit-for-purpose.
Safeguard the creation of high-quality training data for generative AI models in collaboration with the annotation project manager.
Leverage data annotation tools and platforms, including labeling software and data management systems to ensure quality.
Apply domain expertise to inform annotation decisions and ensure high-quality outputs.
Review and further enhance annotation guidelines, and promote the development of standard processes in data annotation.
Rely upon data analysis skills to identify trends, patterns, and anomalies, and make informed decisions on annotation approaches.
Lead on problem-solving to resolve complex annotation challenges and ensure data quality.
Stay up-to-date with industry trends and standard methodologies in data annotation and finance/news.
Be ready to take a hands-on role in project and product coordination when needed- with input from Technical specialist, Annotation manager and Senior annotators.



**You** **u2019ll need to have:**



*Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.


A bacheloru2019s degree or above in Statistics, Data Analytics and Data Science or other STEM related fields.
A minimum of four years of demonstrated experience in data management concepts such as data quality, random sampling and data modeling.
Experience using data visualization tools such as Tableau or Qlik Sense.
Past project/experience analyzing financial datasets or proven past experience working on financial market concepts.
Demonstrable experience in Data Profiling/Analysis using tools such as Python, R, or SQL.
Extensive experience in communicating results in a clear, concise manner using data visualization tools.
Demonstrated ability taking a logical approach and applying critical thinking skills in order to solve problems.



**Weu2019d Love to See:**


Keen interest and familiarity with generative AI frameworks.
Formal knowledge of data governance and data management, supported by industry certifications (e.g. DAMA CDMP, DCAM, etc.)
Keen interest and familiarity with generative AI frameworks.
Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection.
Past project experience using the Agile/Scrum project management methodology.



Does this sound like you?



Apply if you think we're a good match. We'll get in touch to let you know next steps!

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email

Senior Data Management Professional - Data Quality - Data AI





Location





London





Business Area





Data





Ref #










**Description & Requirements**



Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock u2013 from around the world. In Data, we are responsible for delivering this data, news and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes - all while providing customer support to our clients.



**Our Team:**



Data AI contributes to the building of Bloombergu2019s AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. We encourage our internal processes to take advantage of new AI technologies and strengthen Datau2019s role in providing robust domain expertise and influential data artifacts to Bloombergu2019s products. This way, our clients will continue to have high quality data and access to new types of datasets.



**What's the Role?**



A Senior Data Management Professional (DMP) is a key role within our organization responsible for providing domain expertise in both financial concepts and annotation program management, to the development of our AI products. These individuals act as proactive technical leaders by setting the framework in achieving quality and consistency in the evaluation and training datasets for models that power our AI-enhanced products, and delivering scalable governance in annotation program management across Bloomberg Data. Beyond governing data processes and being problem solvers, they are expected to transform the responsibilities of the team and scale the impact beyond what's possible today.



The role in the Data AI Annotation team covers all annotation program components in developing the evaluation and training of AI models at Bloomberg. Being responsible for the quality of the annotated data, and product quality will be a crucial part of the role, with key work spanning ownership around consensus management, adjudication, and instruction and task design. The team is a critical partner in ensuring the stability and growth of the company which relies on bringing new technology to customers with increased interests in Artificial Intelligence.



**Weu2019ll trust you to:**


Create strategies to analyze processes and data quality questions to ensure our datasets are fit-for-purpose.
Safeguard the creation of high-quality training data for generative AI models in collaboration with the annotation project manager.
Leverage data annotation tools and platforms, including labeling software and data management systems to ensure quality.
Apply domain expertise to inform annotation decisions and ensure high-quality outputs.
Review and further enhance annotation guidelines, and promote the development of standard processes in data annotation.
Rely upon data analysis skills to identify trends, patterns, and anomalies, and make informed decisions on annotation approaches.
Lead on problem-solving to resolve complex annotation challenges and ensure data quality.
Stay up-to-date with industry trends and standard methodologies in data annotation and finance/news.
Be ready to take a hands-on role in project and product coordination when needed- with input from Technical specialist, Annotation manager and Senior annotators.



**You** **u2019ll need to have:**



*Please note we use years of experience as a guide, but we certainly will consider applications from all candidates who are able to demonstrate the skills necessary for the role.


A bacheloru2019s degree or above in Statistics, Data Analytics and Data Science or other STEM related fields.
A minimum of four years of demonstrated experience in data management concepts such as data quality, random sampling and data modeling.
Experience using data visualization tools such as Tableau or Qlik Sense.
Past project/experience analyzing financial datasets or proven past experience working on financial market concepts.
Demonstrable experience in Data Profiling/Analysis using tools such as Python, R, or SQL.
Extensive experience in communicating results in a clear, concise manner using data visualization tools.
Demonstrated ability taking a logical approach and applying critical thinking skills in order to solve problems.



**Weu2019d Love to See:**


Keen interest and familiarity with generative AI frameworks.
Formal knowledge of data governance and data management, supported by industry certifications (e.g. DAMA CDMP, DCAM, etc.)
Keen interest and familiarity with generative AI frameworks.
Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection.
Past project experience using the Agile/Scrum project management methodology.



Does this sound like you?



Apply if you think we're a good match. We'll get in touch to let you know next steps!

Bloomberg is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.

Bloomberg is a disability inclusive employer. Please let us know if you require any reasonable adjustments to be made for the recruitment process. If you would prefer to discuss this confidentially, please email