Position: Data Science Consultant
Company: EPAM Systems
Category: Data Science
Experience required: 5y
English level: upper

WHAT YOU'LL DO
- Drive cross-functional EPAM and/or EPAM’s client’s teams to understand challenges and define solutions for EPAM’s clients leveraging AI, Data Science, Machine Learning and Machine Learing Engineering skills
- Work with clients to deliver AI Products providing value to end-users
- Participate and drive EPAM competencies development, work on new EPAM offerings in AI,Data Science, ML and MLE space as well as work on refining existing offerings
- Contribute to location’s growth, both in terms of talent and location capabilities 
- The ultimate candidate would have a strong mathematics background and a desire to work with Machine Learning (ML) technologies hands-on
- Ability to wear many hats at a time and willing to train some of these skills if you bring the passion and desire to grow professionally and technically
- Independent self-motivated worker but team aligned
- Passionate about creating new things using software
- Interested in delivering practical applications of Machine Learning
- Hands-on person with good communication abilities both written and presenting to leadership
- Ability or desire to work closely with DevOps on infrastructure and release planning.

REQUIREMENTS
- Data Science: 3+ years hands-on experience with core Data Science, as well as knowledge of one of the advanced Data Science and AI areas (Computer Vision, NLP, Advanced Analytics etc.) 
- Engineering: Experience delivering AI to production, familiarity and experience with MLOps, Data, Analytics platforms design, development, leadership.
- Leadership: Track record of delivering complex AI-empovered and/or AI-empovering programs to the clients; Experience gorwing the team to scale up Data Science, AI &ML capability 
- Consulting: Experience in exploring business problem and convering it to technology solutions; expertise in pre-sales, solution definition activities 
- Domain Expertise (nice to have): deep knowledge of one or more business domain (e.g. CPG, Retail, Financial Services, Insurance, Healthcare/ Lifescience)
- Typica technologies: Python, ML, AI, Big Data (Hadoop, Spark, Hive, etc.), AWS, Docker, Kubernetes, DB (PlSQL, HQL, Mongo), Azure (Azure ML), Google (Vertex AI), Databricks or similar.