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Data Scientist - Commercial Data Products (Optimization & Pre-Call Intelligence)

Pay
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Work setting
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Employment
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What you’ll work on

Full posting
  • Design, build and validate ML models for commercial optimization and pre-call intelligence

  • Consume Feature Store features and flag gaps to Data Engineering

  • Run exploratory analysis, feature selection and model experiments in Dataiku

  • Deploy and monitor models in production via Dataiku

  • Turn model outputs into business-ready insights for stakeholders

From the employer’s posting
Design, build, and validate ML models for Commercial Optimization and Pre-Call Intelligence use cases
Consume features from the Feature Store (Dataiku/Snowflake); flag gaps back to Data Engineering
Perform exploratory data analysis, feature selection, and model experimentation in Dataiku
Deploy and monitor models in production via Dataiku
Translate model outputs into business-ready insights with product and commercial stakeholders

What you’ll bring

All qualifications

Core experience

  • At least 5 years as a Data Scientist in a commercial enterprise context
  • Hands-on ML model building and deployment in Dataiku (or similar)
  • Strong Python and SQL
  • Solid grounding in statistics and ML fundamentals
  • Comfortable working in governed enterprise environments
Qualification wording
At least 5 years experience as a Data Scientist in a Commercial Enterprise context
Hands-on ML model building and deployment in Dataiku (or similar)
Strong Python and SQL
Solid grounding in statistics and ML fundamentals
Comfortable in governed enterprise environments
Apply at EPAM Systems

Posting record

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Actively hiringFirst seen by us 2 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 1, 20262 days ago
Recorded sightings
4
Last seen by us
Nov 4, 2026
Employer says posted
Oct 7, 2026

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EPAM Systems is hiring

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  • Python
  • SQL
  • Power BI
  • Snowflake
Where the posting names them
You will drive the development of commercial data products for enterprise CDP teams, leveraging AI-enabled engineering excellence and cloud-based innovation labs (Snowflake). In this hybrid role based in Copenhagen, you will use Dataiku, Snowflake, and Power BI to optimize core commercial operations and pre-call intelligence. You will collaborate with engineering and product teams to deliver scalable solutions that improve productivity and quality while reducing long-term costs. This position anchors you in a managed delivery and optimization program, combining technical depth and cross-team partnership. Responsibilities Design, build, and validate ML models for Commercial Optimization and Pre-Call Intelligence use cases Consume features from the Feature Store (Dataiku/Snowflake); flag gaps back to Data Engineering Perform exploratory data analysis, feature selection, and model experimentation in Dataiku Train, tune, and evaluate models Deploy and monitor models in production via Dataiku Translate model outputs into business-ready insights with product and commercial stakeholders Collaborate with Data Engineering, product, and delivery teams Requirements At least 5 years experience as a Data Scientist in a Commercial Enterprise context Hands-on ML model building and deployment in Dataiku (or similar) Strong Python and SQL Solid grounding in statistics and ML fundamentals Comfortable in governed enterprise environments Healthcare, claims, HCP, support-program, or CRM data experience (preferred) Life sciences / pharma commercial analytics background (preferred)

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Job description

View original posting ↗

You will drive the development of commercial data products for enterprise CDP teams, leveraging AI-enabled engineering excellence and cloud-based innovation labs (Snowflake). In this hybrid role based in Copenhagen, you will use Dataiku, Snowflake, and Power BI to optimize core commercial operations and pre-call intelligence. You will collaborate with engineering and product teams to deliver scalable solutions that improve productivity and quality while reducing long-term costs. This position anchors you in a managed delivery and optimization program, combining technical depth and cross-team partnership. Responsibilities Design, build, and validate ML models for Commercial Optimization and Pre-Call Intelligence use cases Consume features from the Feature Store (Dataiku/Snowflake); flag gaps back to Data Engineering Perform exploratory data analysis, feature selection, and model experimentation in Dataiku Train, tune, and evaluate models Deploy and monitor models in production via Dataiku Translate model outputs into business-ready insights with product and commercial stakeholders Collaborate with Data Engineering, product, and delivery teams Requirements At least 5 years experience as a Data Scientist in a Commercial Enterprise context Hands-on ML model building and deployment in Dataiku (or similar) Strong Python and SQL Solid grounding in statistics and ML fundamentals Comfortable in governed enterprise environments Healthcare, claims, HCP, support-program, or CRM data experience (preferred) Life sciences / pharma commercial analytics background (preferred)
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