Senior Data Scientist

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EPAM Systems

Newcastle upon Tyne, UK

Application Deadline

Since 1993, EPAM Systems, Inc. (NYSE: EPAM) has leveraged its advanced software engineering heritage to become the foremost global digital transformation services provider – leading the industry in digital and physical product development and digital platform engineering services. Through its innovative strategy; integrated advisory, consulting, and design capabilities; and unique ‘Engineering DNA,’ EPAM’s globally deployed hybrid teams help make the future real for clients and communities around the world by powering better enterprise, education and health platforms that connect people, optimize experiences, and improve people’s lives. In 2021, EPAM was added to the S&P 500 and included among the list of Forbes Global 2000 companies.

Selected by Newsweek as a 2021 Most Loved Workplace, EPAM’s global multi-disciplinary teams serve customers in more than 45 countries across five continents. As a recognized leader, EPAM is listed among the top 15 companies in Information Technology Services on the Fortune 1000 and ranked as the top IT services company on Fortune’s 100 Fastest-Growing Companies list for the last three consecutive years. EPAM is also listed among Ad Age’s top 25 World’s Largest Agency Companies for three consecutive years, and Consulting Magazine named EPAM Continuum a top 20 Fastest-Growing Firm.


Are you eager to gain new insights from analyzing company data?
Are you passionate about using large data sets to find opportunities for product and process optimization? Are you a person who loves using models to test the effectiveness of different courses of action?
Look no further than EPAM where we live and breathe technology. Make your next career move with us!


  • Perform statistical analysis, hypothesis testing and experimentation
  • Conducting analysis and building predictive and ML models across a broad range of industries
  • Provide unique insights from large volumes of data
  • Create model pipelines for feature engineering, missing value treatment and/or outlier detection
  • Work with ML cloud technologies such as Sagemaker to automate training and monitoring of models
  • Writing high quality Python code according to PEP-8 guidelines
  • Tackle a large range of ML problems from: NLP, deep learning, computer vision, optimisation, risk/fraud, anomaly detection, demand forecasting
  • Tell stories back to the business through stunning data visualisation
  • Work in an agile environment
  • Work with version control systems
  • Provide hands-on leadership, coaching and mentoring to junior members of staff
  • Translate requirements and acceptance criteria into ML implementations
  • Provide estimates for ML activities


  • 3+ years of experience working in a similar role
  • Strong academic background
  • Good programming skills in Python and SQL (other programming languages are a bonus, e.g. R, SAS, Julia)
  • Knowledge of Spark is a plus
  • Familiarity with one of the following: Microsoft Azure, AWS or GCP with specific knowledge of their ML functionality
  • Good understanding of the Data Science Life Cycle
  • Experience with a range of visualisations libraries (matplotlib, seaborn, plotly, bokeh)
  • Solid understanding of common statistical and ML techniques, both classical and deep learning
  • Speciality in one of: classification/regression (GBMs, SVMs, GLMs), forecasting, NLP, deep learning, optimisation
  • Experience with end-to-end ML systems in the cloud, including data processing, feature engineering and tuning of ML models in training and production, with both structured and unstructured data is a plus
  • Knowledge of industry specific third-party data (digital marketing, clickstream, consumer credit risk corporate and sovereign risk, etc.)
  • Understanding business requirements and ability to translate it to ML approaches
  • Ability to take initiative and lead engagements as required


  • We offer a range of benefits including
  • A competitive group pension plan, life assurance and income protection
  • Private medical insurance, private dental care and critical illness cover
  • Cycle scheme Tech scheme and season ticket loan
  • Employee assistance program
  • Unlimited access to LinkedIn learning solutions
  • EPAM Employee Stock Purchase Plan (ESPP) (subject to certain eligibility requirements)
  • Various perks such as Gym discount, Friday lunch, on-site massage and regular social events
  • Some of these benefits may be available only after you have passed your probationary period


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