What Jobs are available for Databases in the United Kingdom?
Showing 9 Databases jobs in the United Kingdom
Senior Data Scientist - Actuarial Modeling
NG1 1HN Nottingham, East Midlands
£75000 Annually
WhatJobs Direct
Posted today
Job Viewed
Job Description
Our client, a leading insurance provider, is seeking a highly skilled Senior Data Scientist with a strong background in actuarial modeling to join their innovative, fully remote analytics team. This role is pivotal in developing sophisticated predictive models and analytical solutions to drive strategic decision-making across the business. You will leverage vast datasets to forecast risk, optimise pricing strategies, enhance underwriting processes, and improve customer retention. The ideal candidate will possess a deep understanding of insurance principles, coupled with advanced expertise in statistical modeling, machine learning, and data mining techniques. Responsibilities will include designing and implementing predictive models for areas such as claims frequency and severity, customer lifetime value, fraud detection, and policy lapse. You will work with a variety of data sources, from structured policyholder data to unstructured text and external economic indicators. Proficiency in programming languages such as Python or R, and experience with SQL and big data technologies (e.g., Spark, Hadoop) are essential. You will be expected to develop and validate models, interpret complex results, and communicate actionable insights to non-technical stakeholders, including senior management and underwriting teams. The ability to translate business challenges into analytical problems and to propose innovative solutions is crucial. This role offers the opportunity to contribute to significant business improvements and directly impact profitability. You will be part of a collaborative, forward-thinking team that embraces a remote-first work culture. The successful applicant will play a key role in shaping the future of insurance analytics, utilising cutting-edge data science methodologies. Mentoring junior data scientists and contributing to the development of best practices within the team will also be a key aspect of the role.
Key Responsibilities:
Key Responsibilities:
- Develop, validate, and deploy advanced statistical and machine learning models for insurance applications.
- Analyse large, complex datasets to identify trends, risks, and opportunities.
- Build predictive models for pricing, underwriting, claims, and customer behaviour.
- Collaborate with actuarial, underwriting, and claims departments to understand business needs.
- Translate complex analytical findings into clear, actionable insights for stakeholders.
- Utilise programming languages like Python or R and SQL for data manipulation and modeling.
- Contribute to the design and implementation of data infrastructure and pipelines.
- Mentor and guide junior data scientists and analysts.
- Stay updated on the latest advancements in data science, machine learning, and insurance analytics.
- Ensure data quality, integrity, and model robustness.
- Master's or PhD in Statistics, Data Science, Mathematics, Actuarial Science, or a related quantitative field.
- 5+ years of experience in data science, with a focus on actuarial modeling or insurance analytics.
- Strong understanding of insurance products, markets, and regulations.
- Proficiency in Python or R, SQL, and experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to explain technical concepts to non-technical audiences.
- Proven ability to work independently and collaboratively in a remote team environment.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
0
Senior Data Scientist - Financial Modeling
EC2N 1HQ London, London
£75000 Annually
WhatJobs Direct
Posted 1 day ago
Job Viewed
Job Description
Our client is a globally recognized financial institution renowned for its innovation in quantitative finance and risk management. We are seeking an exceptional Senior Data Scientist with deep expertise in financial modeling to join our prestigious team in the heart of London, England, UK . This role is crucial for developing sophisticated predictive models, risk assessment tools, and algorithmic trading strategies that drive significant business value and competitive advantage. You will be working with vast datasets, advanced statistical techniques, and cutting-edge machine learning algorithms in a challenging and collaborative environment.
Responsibilities:
Responsibilities:
- Design, develop, and implement advanced statistical and machine learning models for financial forecasting, risk management, fraud detection, and algorithmic trading.
- Clean, process, and transform large, complex financial datasets from various sources.
- Conduct rigorous quantitative analysis to identify patterns, trends, and insights within financial markets and customer behavior.
- Develop and validate predictive models, ensuring their accuracy, robustness, and performance.
- Collaborate closely with portfolio managers, traders, risk officers, and other business stakeholders to understand their needs and deliver tailored data-driven solutions.
- Communicate complex analytical findings and model methodologies effectively to both technical and non-technical audiences.
- Stay abreast of the latest research in data science, machine learning, and financial econometrics.
- Contribute to the development and improvement of the firm's data infrastructure and modeling tools.
- Mentor junior data scientists and contribute to the team's technical growth.
- Ensure compliance with regulatory requirements and ethical standards in all modeling activities.
- A Master's or PhD degree in a quantitative field such as Statistics, Mathematics, Computer Science, Physics, Economics, or Financial Engineering.
- A minimum of 5 years of experience in data science or quantitative analysis, with a significant focus on financial modeling within the financial services industry.
- Proven expertise in developing and deploying machine learning models (e.g., regression, classification, time series analysis, deep learning).
- Proficiency in programming languages commonly used in data science, such as Python (with libraries like Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) and SQL.
- Strong understanding of financial markets, instruments, and risk management principles.
- Excellent analytical, problem-solving, and critical thinking skills.
- Superb communication and presentation skills, with the ability to explain complex technical concepts clearly.
- Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Knowledge of financial regulations and compliance frameworks.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
1
Senior Data Scientist (Financial Modeling)
PL1 1AB Plymouth, South West
£80000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client is a leading financial services firm seeking a highly skilled Senior Data Scientist with expertise in Financial Modeling to join their innovative, fully remote team. This role will be instrumental in developing and refining sophisticated quantitative models that drive critical business decisions. The successful candidate will leverage advanced statistical techniques, machine learning algorithms, and big data technologies to analyze complex financial datasets, identify trends, and generate actionable insights. Responsibilities include designing, building, testing, and deploying predictive models for areas such as risk assessment, fraud detection, portfolio optimization, and market forecasting. You will work closely with stakeholders across finance, product, and technology departments to understand their analytical needs and translate them into data-driven solutions. A strong understanding of financial markets, regulatory requirements, and risk management principles is essential. The Senior Data Scientist will also be responsible for communicating complex analytical findings to both technical and non-technical audiences through clear visualizations and compelling narratives. This remote position requires exceptional self-discipline, strong problem-solving skills, and the ability to work independently while collaborating effectively with a distributed team. We are looking for an analytical powerhouse with a passion for finance and data science, who can contribute significantly to the company's strategic objectives through rigorous quantitative analysis and innovative modeling techniques. The ability to mentor junior data scientists and contribute to the team's overall technical growth will be highly valued. This is an outstanding opportunity to work on challenging problems in a dynamic and collaborative remote environment.
Responsibilities:
Responsibilities:
- Develop, validate, and deploy advanced quantitative and financial models.
- Analyze large, complex datasets to identify trends, patterns, and anomalies.
- Apply machine learning and statistical techniques to solve business problems in finance.
- Collaborate with finance and business teams to define analytical requirements.
- Communicate complex findings and recommendations to stakeholders through reports and presentations.
- Ensure the accuracy, robustness, and scalability of deployed models.
- Stay abreast of the latest advancements in data science, machine learning, and financial modeling.
- Mentor junior data scientists and contribute to knowledge sharing within the team.
- Implement best practices for data management, model versioning, and deployment.
- Contribute to the strategic direction of data science initiatives.
- Master's or PhD in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, or Finance.
- Minimum of 6 years of experience in data science, with a focus on financial modeling.
- Proven expertise in developing and implementing predictive models using Python or R.
- Strong knowledge of machine learning algorithms and statistical modeling techniques.
- Experience with financial data sources and markets.
- Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent communication, presentation, and interpersonal skills for remote collaboration.
- Demonstrated ability to work independently and manage multiple projects simultaneously.
- Experience with data visualization tools (e.g., Tableau, Power BI).
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
2
Senior Data Scientist - Reservoir Modeling
G2 1DH Glasgow, Scotland
£70000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client, a pioneering energy exploration company, is seeking a highly analytical and innovative Senior Data Scientist specializing in Reservoir Modeling to join their fully remote team. This role is critical for optimizing subsurface resource extraction and maximizing production efficiency through advanced data analytics and predictive modeling. You will leverage vast datasets from geological surveys, seismic imaging, well logs, and production history to build and refine sophisticated reservoir simulation models. The ideal candidate will possess a strong background in data science, machine learning, statistical modeling, and a deep understanding of petroleum geology or reservoir engineering principles. Your responsibilities will include developing and implementing machine learning algorithms for reservoir characterization, forecasting production decline curves, predicting hydrocarbon saturation, and identifying optimal well placement strategies. You will also be responsible for data wrangling, feature engineering, model validation, and communicating complex findings to multidisciplinary teams, including geologists, reservoir engineers, and management. This is a remote-first position, requiring exceptional self-discipline, communication skills, and the ability to collaborate effectively across different time zones using virtual collaboration tools. A proven track record of applying data science techniques to solve complex problems in the oil and gas sector, particularly in reservoir characterization and simulation, is essential. Experience with large-scale data processing, cloud computing platforms (AWS, Azure, GCP), and programming languages such as Python or R, along with relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn), is required. A Ph.D. or Master's degree in a quantitative field such as Data Science, Computer Science, Petroleum Engineering, or Geology with a strong data analytics focus is highly desirable. Join us in shaping the future of energy exploration through cutting-edge data science.
Responsibilities:
Responsibilities:
- Develop, implement, and validate advanced reservoir simulation models using data science and machine learning techniques.
- Analyze geological, geophysical, and production data to characterize subsurface reservoirs.
- Build predictive models for hydrocarbon recovery, production forecasting, and uncertainty quantification.
- Apply machine learning algorithms for tasks such as seismic interpretation, core analysis, and well log analysis.
- Perform data cleaning, feature engineering, and data pipeline development for large datasets.
- Collaborate with geologists, reservoir engineers, and production teams to integrate model insights into operational decisions.
- Present complex analytical results and recommendations to technical and non-technical stakeholders.
- Stay current with advancements in data science, machine learning, and their applications in the energy sector.
- Optimize computational workflows for large-scale reservoir modeling.
- Master's or Ph.D. in Data Science, Computer Science, Petroleum Engineering, Geology, or a related quantitative field.
- Proven experience as a Data Scientist in the oil and gas industry, with a focus on reservoir modeling or characterization.
- Strong expertise in statistical modeling, machine learning algorithms, and deep learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
- Proficiency in programming languages: Python (with libraries like Pandas, NumPy, SciPy) and/or R.
- Experience with reservoir simulation software and geological modeling tools.
- Familiarity with big data technologies and cloud computing platforms (AWS, Azure, GCP).
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills for remote collaboration.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
3
Lead Data Scientist - Financial Modeling
SR1 2AA Sunderland, North East
£80000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client, a leading financial institution, is looking for a highly skilled Lead Data Scientist to spearhead their advanced financial modeling initiatives. This fully remote role offers an exceptional opportunity to work on cutting-edge projects from the comfort of your home office, contributing significantly to our strategic decision-making processes. You will be at the forefront of developing sophisticated predictive models, risk assessment frameworks, and anomaly detection systems that drive profitability and mitigate financial risks.
As the Lead Data Scientist, you will guide a team of talented data scientists, fostering an environment of collaboration and technical excellence. Your responsibilities will encompass the entire data science lifecycle, from data acquisition and cleaning to model development, validation, and deployment. A deep understanding of machine learning algorithms, statistical modeling, and time-series analysis is crucial. Experience with financial markets, quantitative finance, and regulatory compliance is highly advantageous. You will leverage your expertise in Python or R, along with libraries like TensorFlow, PyTorch, scikit-learn, and Pandas, to build robust and scalable solutions. Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop) are also essential for handling large financial datasets.
We expect candidates to possess a Master's or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Physics. A minimum of 6 years of relevant industry experience, with a proven track record in financial modeling and a leadership capacity, is required. Excellent communication and presentation skills are vital for conveying complex findings to both technical and non-technical stakeholders. You will be instrumental in shaping our data-driven strategy, providing actionable insights that enhance financial performance and operational efficiency. This is a unique chance to make a substantial impact in a globally recognized financial organization, working remotely.
As the Lead Data Scientist, you will guide a team of talented data scientists, fostering an environment of collaboration and technical excellence. Your responsibilities will encompass the entire data science lifecycle, from data acquisition and cleaning to model development, validation, and deployment. A deep understanding of machine learning algorithms, statistical modeling, and time-series analysis is crucial. Experience with financial markets, quantitative finance, and regulatory compliance is highly advantageous. You will leverage your expertise in Python or R, along with libraries like TensorFlow, PyTorch, scikit-learn, and Pandas, to build robust and scalable solutions. Proficiency in SQL and experience with big data technologies (e.g., Spark, Hadoop) are also essential for handling large financial datasets.
We expect candidates to possess a Master's or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or Physics. A minimum of 6 years of relevant industry experience, with a proven track record in financial modeling and a leadership capacity, is required. Excellent communication and presentation skills are vital for conveying complex findings to both technical and non-technical stakeholders. You will be instrumental in shaping our data-driven strategy, providing actionable insights that enhance financial performance and operational efficiency. This is a unique chance to make a substantial impact in a globally recognized financial organization, working remotely.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
4
Senior Data Scientist - Financial Modeling
SR1 1 Sunderland, North East
£70000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client, a highly respected financial services institution, is seeking an experienced Senior Data Scientist to lead the development and implementation of advanced financial models. This is a fully remote position, enabling you to contribute your expertise from anywhere in the UK. You will play a crucial role in leveraging data to drive strategic decision-making, optimize risk management, and enhance predictive capabilities within the firm.
Key Responsibilities:
Key Responsibilities:
- Develop, validate, and deploy sophisticated predictive models for areas such as credit risk, market risk, fraud detection, and customer behavior analysis.
- Clean, transform, and analyze large, complex datasets from various sources using statistical and machine learning techniques.
- Collaborate closely with business stakeholders, data engineers, and other data scientists to understand requirements and deliver actionable insights.
- Design and implement A/B tests and other experimental methodologies to evaluate model performance and business impact.
- Stay abreast of the latest advancements in data science, machine learning, and financial modeling techniques.
- Build robust data pipelines and automated reporting systems to support ongoing model monitoring and performance tracking.
- Communicate complex findings and model methodologies clearly and concisely to both technical and non-technical audiences.
- Mentor junior data scientists and contribute to the growth and development of the data science team.
- Ensure compliance with all relevant regulations and data privacy standards.
- Contribute to the strategic roadmap for data science initiatives within the organization.
- Document all modeling processes, assumptions, and results thoroughly.
- Master's or Ph.D. in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
- Minimum of 5 years of experience as a Data Scientist, with a significant focus on financial modeling and analysis.
- Proven expertise in developing and deploying machine learning models (e.g., regression, classification, time-series forecasting, clustering).
- Proficiency in programming languages such as Python or R, and strong experience with relevant libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
- Solid understanding of statistical concepts and methods.
- Experience with SQL and working with relational databases; experience with big data technologies (e.g., Spark, Hadoop) is a plus.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong communication and presentation skills, with the ability to explain technical concepts to diverse audiences.
- Familiarity with financial industry regulations and data governance principles.
- Ability to work independently and effectively manage projects in a remote setting.
- Demonstrated ability to translate business problems into data science solutions.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
5
Remote Lead Data Scientist - Financial Modeling
NE1 4XX Newcastle upon Tyne, North East
£75000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client is seeking an exceptional Remote Lead Data Scientist with a specialization in financial modeling to join their innovative banking and finance team. This is a crucial, remote-first role where you will lead the development and implementation of advanced statistical models and machine learning algorithms to drive data-informed decision-making. You will guide a team of data scientists, mentor junior members, and collaborate with cross-functional teams to solve complex financial challenges.
Responsibilities:
Responsibilities:
- Lead the design, development, and deployment of sophisticated financial models and predictive analytics solutions.
- Utilize machine learning, statistical modeling, and data mining techniques to extract actionable insights from large datasets.
- Mentor and manage a team of data scientists, providing technical guidance, code reviews, and performance feedback.
- Collaborate with business stakeholders to understand their requirements and translate them into data science projects.
- Develop and implement robust data pipelines and ensure data quality and integrity for modeling purposes.
- Stay abreast of the latest advancements in data science, machine learning, and financial modeling techniques.
- Communicate complex findings and recommendations effectively to both technical and non-technical audiences.
- Contribute to the strategic direction of the data science function within the organization.
- Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.
- Extensive experience (7+ years) as a Data Scientist, with a significant focus on financial modeling, risk management, or quantitative finance.
- Proven leadership experience, managing and mentoring data science teams.
- Expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
- Strong knowledge of SQL and experience working with large databases and distributed computing frameworks (e.g., Spark).
- Demonstrated ability to develop and deploy machine learning models into production environments.
- Excellent problem-solving skills and a strong understanding of statistical principles.
- Outstanding communication and presentation skills, with the ability to articulate complex technical concepts clearly.
- Experience working in a fully remote, collaborative environment is highly preferred.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
Be The First To Know
About the latest Databases Jobs in United Kingdom !
6
Lead Data Scientist - Financial Risk Modeling
LS1 1 Leeds, Yorkshire and the Humber
£70000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client is seeking an experienced and visionary Lead Data Scientist to spearhead their financial risk modeling initiatives. This is a fully remote opportunity, allowing you to contribute your expertise from anywhere. You will be responsible for developing and implementing advanced statistical and machine learning models to assess, predict, and mitigate various financial risks, including credit risk, market risk, and operational risk. This role requires a deep understanding of financial regulations and a passion for leveraging data to drive sound financial decision-making.
Responsibilities:
Qualifications:
This is an exciting opportunity to shape the future of risk management within a forward-thinking financial organization, all while enjoying the flexibility of a remote work environment. Join us and make a significant impact.
Responsibilities:
- Lead the design, development, validation, and implementation of sophisticated risk models using statistical and machine learning techniques.
- Collaborate with risk management, compliance, and business units to identify key risk drivers and modeling requirements.
- Mentor and guide a team of data scientists, fostering a culture of innovation and technical excellence.
- Stay updated on regulatory changes and industry best practices in financial risk management.
- Develop robust methodologies for model monitoring, performance evaluation, and recalibration.
- Extract, clean, and transform complex financial datasets from various sources.
- Present findings and model insights to senior management and regulatory bodies.
- Ensure model documentation is comprehensive, accurate, and compliant with regulatory standards.
- Evaluate and adopt new technologies and methodologies to enhance the firm's risk modeling capabilities.
- Champion data-driven decision-making across the organization regarding risk assessment.
Qualifications:
- Master's or Ph.D. in Statistics, Econometrics, Mathematics, Data Science, or a related quantitative field.
- Extensive experience (7+ years) in financial risk modeling, with a proven track record of leading complex projects.
- Proficiency in statistical modeling, machine learning algorithms (e.g., regression, classification, clustering, time series forecasting), and deep learning.
- Strong programming skills in Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
- Experience with SQL for data querying and manipulation.
- Solid understanding of financial products, markets, and regulatory frameworks (e.g., Basel Accords, IFRS 9).
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong leadership and team management capabilities.
- Effective communication and presentation skills, with the ability to explain complex technical concepts to diverse audiences.
- Experience with data visualization tools is a plus.
This is an exciting opportunity to shape the future of risk management within a forward-thinking financial organization, all while enjoying the flexibility of a remote work environment. Join us and make a significant impact.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
7
Senior Data Scientist - Financial Risk Modeling
EC2N 1DL London, London
£85000 Annually
WhatJobs Direct
Posted 2 days ago
Job Viewed
Job Description
Our client, a leading financial institution, is seeking a highly accomplished Senior Data Scientist to join their risk management division. This is a fully remote opportunity, allowing you to contribute to critical projects from anywhere. You will be at the forefront of developing and implementing advanced statistical and machine learning models to assess and mitigate financial risks, including credit risk, market risk, and operational risk. Your expertise will directly influence strategic decision-making and regulatory compliance. Key responsibilities include:
The ideal candidate will possess a Ph.D. or Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Economics, or a related field. Extensive experience in data science, with a strong focus on financial risk modeling within the banking or finance sector, is essential. Proven proficiency in Python or R, along with experience in SQL and big data technologies (e.g., Spark, Hadoop), is required. Familiarity with cloud platforms (AWS, Azure, GCP) is a plus. Excellent understanding of various machine learning algorithms (e.g., regression, classification, clustering, deep learning) and statistical modeling techniques is mandatory. Strong communication and presentation skills are vital for presenting findings to diverse audiences. As this role is remote, you must demonstrate exceptional self-management and collaboration skills.
- Designing, building, and deploying sophisticated predictive models for financial risk assessment using machine learning and statistical techniques.
- Analyzing large, complex datasets to identify trends, patterns, and potential risk factors.
- Validating and monitoring the performance of existing risk models, implementing improvements as needed.
- Collaborating with risk managers, quants, and IT teams to integrate models into production systems.
- Developing new methodologies for risk measurement and stress testing.
- Communicating complex technical findings to non-technical stakeholders, including senior management.
- Staying current with regulatory requirements (e.g., Basel III/IV) and industry best practices in risk modeling.
- Mentoring junior data scientists and contributing to the team's technical growth.
- Researching and applying novel data science techniques to enhance risk management capabilities.
The ideal candidate will possess a Ph.D. or Master's degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, Economics, or a related field. Extensive experience in data science, with a strong focus on financial risk modeling within the banking or finance sector, is essential. Proven proficiency in Python or R, along with experience in SQL and big data technologies (e.g., Spark, Hadoop), is required. Familiarity with cloud platforms (AWS, Azure, GCP) is a plus. Excellent understanding of various machine learning algorithms (e.g., regression, classification, clustering, deep learning) and statistical modeling techniques is mandatory. Strong communication and presentation skills are vital for presenting findings to diverse audiences. As this role is remote, you must demonstrate exceptional self-management and collaboration skills.
Is this job a match or a miss?
This advertiser has chosen not to accept applicants from your region.
8