Senior I Data Scientist

Stack

Responsibilities

• ▹Explore operational and financial data, frame hypotheses and test them
• ▹Build predictive and analytical models: delays and durations, congestion, cost, plan-versus-actual variance
• ▹Engineer features over curated data layers and document their meaning and provenance
• ▹Work with historical data states so that a training sample reflects what was known at the time of the event
• ▹Prepare inputs for analytics products: KPI dashboards, user activity analytics, executive summaries, trend analysis
• ▹Align metric and calculation definitions with the semantic layer so figures agree across reports, APIs and interfaces
• ▹Validate results with business stakeholders and produce model documentation

Requirements

• ▹Analytical Python: pandas, scikit-learn, statistical libraries, clear visualisation
• ▹Spark SQL and PySpark, confident work on large tables, window functions, understanding of distributed execution
• ▹Databricks as a working environment: notebooks, jobs, experiment tracking, catalog and data permissions, table versions and time travel
• ▹Understanding of the medallion model and which layer is the correct source for an analysis
• ▹Statistics and time-series methods, sound experiment design, baselines and honest quality metrics
• ▹Experience with raw data from enterprise systems of record: gaps, duplicates, retroactive corrections, inconsistent reference data
• ▹Ability to explain and defend a result to a non-technical stakeholder

Nice to have

• ▹Storing features in the catalog and handing them to the production path
• ▹Transportation, logistics or supply chain
• ▹Geospatial analysis and route data
• ▹Experience handing a model over to an ML engineer for production

Soft skills

About the company

Established in 1997, Softeq specialises in new product development and R&D, tackling difficult technology problems, and also offers early-stage innovation and digital transformation consulting on a global scale.