Data Scientist — Remote & Flexible Hours, ML & Product Impact

Inovetix

Chicago (IL)

Hybrid

USD 120,000 - 165,000

Full time

14 days+

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Benefits offered by this job

Competitive salary
Flexible hours
Remote-friendly culture
Large-scale datasets access
Education budget

Job summary

Inovetix is seeking a Data Scientist to transform product telemetry and customer signals into actionable insights, models, and product improvements. You'll collaborate with PMs and engineers to ship data-driven features end-to-end.

You will design experiments, build models for recommendations and segmentation, and develop dashboards that surface across the organization, while partnering with engineering to productionize models and monitor performance.

Qualifications

  • 4+ years of applied data science experience.
  • Strong Python and SQL skills; comfort with one of pandas / Polars / Spark.
  • Hands-on experience training and evaluating ML models.
  • Familiarity with experimentation methodology (A/B testing, causal inference).
  • Background in statistics, computer science, or a quantitative field.

Responsibilities

  • Design and run experiments that inform product and business decisions.
  • Build models that power recommendations, segmentation, and predictive features.
  • Develop dashboards and reports that surface insight across the org.
  • Partner with engineering to productionize models and monitor their performance.
  • Communicate findings clearly to technical and non-technical audiences.

Skills

Python
SQL
ML modeling
Experimentation

Education

Statistics background
CS or quantitative field

Tools

Pandas
Polars
Spark

Job description

Inovetix is seeking a Data Scientist to transform product telemetry and customer signals into actionable insights, models, and product improvements. You'll collaborate with PMs and engineers to ship data-driven features end-to-end.

You will design experiments, build models for recommendations and segmentation, and develop dashboards that surface across the organization, while partnering with engineering to productionize models and monitor performance.

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