Senior Applied Data Scientist / ML Engineer
New
W
WorkWaveOperational intelligence
Remote (UK-based)Full-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 5+ years in applied data science, ML engineering, or data engineering that included owning models in production
- Required Skills
- AWSPythonSQLSnowflakedbtscikit-learn
Requirements
- Have 5+ years of experience in applied data science, ML engineering, or data engineering that included owning models in production.
- Have built and shipped at least one model into a real product.
- Demonstrate strong Python skills and experience with applied ML libraries for tabular problems.
- Have solid SQL expertise.
- Have depth in supervised learning, forecasting, ranking, recommendation, or optimisation.
- Have experience modelling messy operational data.
- Be able to build data models and feature pipelines using dbt and Snowflake.
- Have experience with deployment, monitoring, and drift detection for models.
- Have experience working with AWS.
- Have quantified the business impact of a shipped model, such as adoption, outcomes, or ROI.
- Be able to explain technical trade-offs to product, engineering, and non-technical business stakeholders.
Responsibilities
- Frame ambiguous customer problems and determine whether machine learning is an appropriate solution.
- Learn the operational domain and the meaning of customer data.
- Build required features and data models using Snowflake and dbt.
- Develop and ship models into real product workflows.
- Work with Product Managers and Software Engineers to make model outputs understandable and usable by customers.
- Define offline and online evaluation for model quality, drift, and reliability.
- Design A/B tests or causal analyses to assess customer outcomes.
- Deploy, test, version, monitor, and detect drift in models.
- Measure and report model adoption, customer outcomes, and business impact.
View Full Description & ApplyYou'll be redirected to the employer's site
