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Sr Applied Data Scientist/Engineer, Decision Intelligence
WorkwaveField Service company
Verona, ItalySenior
Hg
TA Associates Management
EQT Private Equity
Serent Capital
Data & AINew
About the role
TL;DR
Build data products that measurably improve customer decision-making.
- •We are looking for a product-minded applied data scientist or engineer to turn raw operational data into products that measurably improve how our customers make decisions and run their businesses.
- •This is not a research-only role, nor a service-oriented internal analytics position—and it is not a role for a model builder alone.
- •Key Responsibilities Own the Outcome: Take an ambiguous customer problem, decide whether ML is even the right answer, build it, and stay with it until customers are acting on it.
- •Build the Data You Need: When the features don't exist, create them in Snowflake and dbt rather than waiting for someone else to.
- •Make the Value Legible: Decide how a prediction reaches the customer so they understand it, trust it, and act on it.
- •Ship and Operate: Deployment, testing, versioning, monitoring, and drift detection.
- •Requirements 5+ years in applied data science, ML engineering, or data engineering that included owning models in production.
- •Strong Python and applied ML libraries for tabular problems (scikit-learn, XGBoost or LightGBM, statsmodels or Prophet).
- •Solid SQL expertise is required.
- •Depth in supervised learning, forecasting, ranking, recommendation, or optimization.
- •Experience building data pipelines, deployment, monitoring, and drift detection.
Required skills
PythonSQLscikit-learndbtSnowflakeAWS
Nice-to-have skills
LLMs
Tech stack
PythonSQLSnowflakedbtAWSscikit-learn