614 Big Data Analytics jobs in the United Kingdom

• Develop and implement predictive models to forecast equipment maintenance needs, production yields, and potential safety hazards.
• Clean, process, and transform large, complex datasets from various mining operations (e.g., geological, operational, sensor data).
• Design and conduct A/B tests and other statistical experiments to evaluate the impact of process changes.
• Create insightful data visualisations and dashboards to communicate findings to non-technical stakeholders.
• Collaborate with operations managers, engineers, and geologists to understand their challenges and identify opportunities for data-driven solutions.
• Stay abreast of the latest advancements in data science, machine learning, and their applications in the mining industry.
• Develop and maintain robust data pipelines and ETL processes.
• Contribute to the development of data governance policies and best practices.
• Present findings and recommendations clearly and concisely, supported by strong data evidence.
• Actively participate in remote team meetings and contribute to a collaborative virtual work environment.

• MSc or Ph.D. in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field.
• Proven experience as a Data Scientist, with a strong portfolio of data-driven projects.
• Proficiency in programming languages such as Python or R, and associated data science libraries (e.g., Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).
• Strong experience with SQL for data extraction and manipulation.
• Familiarity with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent understanding of statistical modelling, machine learning algorithms (regression, classification, clustering, deep learning), and data mining techniques.
• Experience with data visualisation tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Strong analytical and problem-solving skills with the ability to think critically.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to a diverse audience.
• Demonstrated ability to work independently and manage time effectively in a remote setting.
• Prior experience or a keen interest in the mining or natural resources sector is highly desirable.

• Develop and implement sophisticated statistical models and machine learning algorithms to analyze complex mining data.
• Identify key performance indicators and predictive insights to optimize exploration, extraction, and processing operations.
• Collaborate with geologists, engineers, and operations managers to translate business challenges into data science solutions.
• Design and conduct A/B tests and other experiments to validate model performance and operational impacts.
• Clean, preprocess, and transform large, disparate datasets from various sources (e.g., sensors, geological surveys, operational logs).
• Develop data visualization dashboards and reports 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 industry.
• Mentor junior data scientists and contribute to the growth of the data science team.
• Ensure data integrity, security, and ethical use of data across all analytical projects.
• Propose and develop new analytical methodologies and tools to address emerging industry needs.
• Present findings and recommendations to senior management to inform strategic decision-making.

• Master's or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field.
• 5+ years of experience as a Data Scientist, with a strong preference for experience in the mining, energy, or heavy industry sectors.
• Expertise in programming languages such as Python or R, and proficiency with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy).
• Strong experience with SQL and database management.
• Proven ability to develop and deploy machine learning models (e.g., regression, classification, clustering, time-series forecasting, anomaly detection).
• Experience with big data technologies (e.g., Spark, Hadoop) is a plus.
• Excellent data visualization skills (e.g., Matplotlib, Seaborn, Tableau, Power BI).
• Outstanding analytical, problem-solving, and critical thinking skills.
• Exceptional communication and interpersonal skills, with the ability to explain complex technical concepts clearly.

• Responsible for data analysis, entry and Validation related activities across the Pirbright manufacturing facility, to enable the large scale production of FMD and BTV antigen and finished product in a timely and cost effective manner.
• Analyse production data to identify trends, deviations, and performance metrics.
• Assist in the execution of cleaning validation protocols in line with GMP requirements.
• Bring in SQL / Power BI approaches to improve the site approach to data.
• Support sampling, documentation, and coordination of validation activities.

• GMP experience is essential
• Have a scientific or engineering discipline degree (e.g., Biochemistry, Biotechnology, Chemical Engineering, Pharmaceutical Sciences).
• Understanding of cleaning validation principles and documentation practices.
• Experience with data handling and analytics
• Knowledge of HSE, bio-safety standards, GMP regulations as well as main tools and principles of operational excellence

• Responsible for data analysis, entry and Validation related activities across the Pirbright manufacturing facility, to enable the large scale production of FMD and BTV antigen and finished product in a timely and cost effective manner.
• Analyse production data to identify trends, deviations, and performance metrics.
• Assist in the execution of cleaning validation protocols in line with GMP requirements.
• Bring in SQL / Power BI approaches to improve the site approach to data.
• Support sampling, documentation, and coordination of validation activities.

• GMP experience is essential
• Have a scientific or engineering discipline degree (e.g., Biochemistry, Biotechnology, Chemical Engineering, Pharmaceutical Sciences).
• Understanding of cleaning validation principles and documentation practices.
• Experience with data handling and analytics
• Knowledge of HSE, bio-safety standards, GMP regulations as well as main tools and principles of operational excellence

• Assist in collecting, cleaning, and processing large datasets.
• Perform data analysis to identify trends, patterns, and insights.
• Develop data visualisations and reports to communicate findings.
• Support senior analysts in various data-related projects.
• Learn and apply statistical methods and analytical techniques.
• Gain proficiency in data analysis tools and software (SQL, Python, R).
• Collaborate with team members in a remote setting.
• Contribute to documentation and knowledge sharing.
• Participate actively in training sessions and workshops.
• Help to ensure data accuracy and integrity.

• Recent graduate with a degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Economics, Engineering).
• Strong analytical and problem-solving abilities.
• Aptitude for working with numbers and data.
• Basic understanding of statistical concepts is beneficial.
• Familiarity with programming languages like Python or R is a plus.
• Excellent written and verbal communication skills.
• Ability to work independently and manage time effectively.
• Strong attention to detail.
• Enthusiasm for learning and developing data analysis skills.
• Access to a reliable internet connection for remote work.

• Leading forensic accounting investigations involving large and complex datasets.
• Developing and applying data analytics techniques to detect fraud, money laundering, and other financial irregularities.
• Utilizing forensic accounting software and data visualization tools (e.g., ACL, IDEA, Tableau) for analysis and reporting.
• Performing detailed financial analysis to quantify economic damages and support litigation.
• Extracting, transforming, and analyzing data from various sources, including accounting systems and databases.
• Preparing comprehensive forensic reports and executive summaries.
• Serving as an expert witness in legal proceedings, presenting findings clearly and effectively.
• Collaborating with legal counsel and clients to understand investigative objectives and requirements.
• Mentoring and guiding junior forensic accountants and analysts.
• Staying current with emerging trends in data analytics, cybersecurity, and forensic accounting.

• Lead the design, development, implementation, and maintenance of scalable bioinformatics pipelines for next-generation sequencing (NGS) data analysis (e.g., WGS, WES, RNA-Seq).
• Analyse and interpret complex genomic and transcriptomic datasets to identify genetic variants, gene expression patterns, and other biologically relevant insights.
• Collaborate closely with biologists, geneticists, clinicians, and computational scientists to define project goals and analytical strategies.
• Develop and apply statistical and machine learning methods for genomic data analysis.
• Ensure the quality, reproducibility, and documentation of all bioinformatics analyses and workflows.
• Stay abreast of the latest advancements in bioinformatics, genomics, and related computational fields.
• Mentor and guide junior bioinformaticians and data analysts.
• Contribute to research proposals, grant applications, and publications.
• Manage data storage, processing, and computational resources effectively.
• Present findings to scientific teams and external collaborators.

• PhD in Bioinformatics, Computational Biology, Genetics, Computer Science, or a related quantitative field.
• Minimum of 6 years of post-doctoral or industry experience in bioinformatics, with a strong focus on genomics data analysis.
• Extensive experience with NGS data processing and analysis pipelines (e.g., BWA, GATK, STAR, Salmon).
• Proficiency in programming languages such as Python, R, and shell scripting.
• Strong knowledge of statistical methods and machine learning techniques applicable to genomics.
• Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Singularity) is highly desirable.
• Proven ability to manage complex projects and lead a small team.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and presentation skills, with a track record of publications.
• Ability to work independently and collaboratively in a remote research environment.

At Tata Technologies we make product development dreams a reality by designing, engineering and validating the products of tomorrow for the worlds leading manufacturers. Due to our continued growth we are now recruiting for a Data Analysis Engineer SOX Algorithm to be based at our customers site in Gaydon .

Our Embedded Systems Solutions department (ESS) encompasses all activities outlined under th.

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