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Data Scientist - Commercial Data Products (Optimization & Pre-Call Intelligence)
- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingDesign, 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 qualificationsCore 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
Posting record
Report an errorActively 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
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
EPAM Systems is hiring
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Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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)
Your next step
Complete your application on careers.epam.com. The employer’s form will show what is required.
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About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
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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Denmark
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