Senior I Data Scientist

Softeq

Warszawa

Vor Ort

PLN 120.000 - 190.000

Vollzeit

Vor 8 Tagen

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Zusammenfassung

Softeq in Warsaw, Poland seeks a data analytics professional to explore operational data, build predictive models, and prepare KPI dashboards. The role emphasizes Python (pandas, scikit-learn), Spark SQL, PySpark, and Databricks, ensuring lineage and reproducibility.

You will validate results with stakeholders, document models, and collaborate across teams on data-driven decision making. Familiarity with medallion data architecture and time-series metrics is a plus.

Qualifikationen

  • Analytical Python with pandas and scikit-learn.
  • Spark SQL and PySpark for large tables.
  • Databricks environment experience.
  • Understanding of medallion data model and historical state handling.
  • Statistics and time-series methods; solid experimental design.
  • Experience with enterprise data from systems of record.
  • Ability to explain results to non-technical stakeholders.

Aufgaben

  • Explore operational and financial data, frame hypotheses and test them.
  • Build predictive and analytical models for delays, durations, congestion, costs, and plan-versus-actual variance.
  • Engineer features over curated data and document their provenance.
  • Prepare inputs behind analytics products: KPI dashboards and executive summaries.
  • Align metric definitions with the semantic layer across reports, APIs and interfaces.
  • Validate results with business stakeholders and produce model documentation.

Kenntnisse

Python
Pandas
Scikit-learn
Spark SQL
PySpark
Databricks
Time-series
Modeling
Data visualization
Stakeholder communication

Tools

Databricks
SQL

Jobbeschreibung

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 abuse@softeq.com

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