EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities.
We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow.
No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
Are you eager 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!
What You’ll Do
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
What You Have
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
Various perks such as Friday lunch, on-site massage and regular social events
Unlimited access to LinkedIn learning solutions
EPAM Employee Stock Purchase Plan (ESPP) (subject to certain eligibility requirements)
Some of these benefits may be available only after you have passed your probationary period