Senior I Data Scientist

Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!

As we're expecting to expand our team and launch new projects within the next 1-2 months, we're already accepting applications and starting the interview process for selected candidates. We'd love to hear from you - feel free to apply!

What the role does here

• Explores operational and financial data, frames hypotheses and tests them;
• Builds predictive and analytical models: delays and durations, congestion, cost, plan-versus-actual variance;
• Engineers features over the curated data layers and documents their meaning and provenance;
• Works with historical data states so that a training sample reflects what was known at the time of the event rather than what is known now;
• Prepares the inputs behind analytics products: KPI dashboards, user activity analytics, executive summaries, trend analysis;
• Aligns metric and calculation definitions with the semantic layer so figures agree across reports, APIs and interfaces;
• Validates results with business stakeholders and produces model documentation.

Must have

• Analytical Python: pandas, scikit-learn, statistical libraries, clear visualization;
• Spark SQL and PySpark, confident work on large tables, window functions, and an 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 a given 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.

Softeq communicates only from @softeq.com email addresses. We never request payments or fees for any reason during hiring - including trainings or courses to be completed, equipment, onboarding, or background checks - and we will not ask for banking information, cryptocurrency or gift cards. If you receive a message from any other domain or requesting payment, do not respond and report it to [email protected]