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Senior Data Scientist

Data ScientistData ScientistFull TimeRemoteTeam 201-500Since 2014H1B SponsorCompany SiteLinkedIn

Location

Connecticut + 3 moreAll locations: Connecticut, New Jersey, New York, Massachusetts

Posted

30 days ago

Salary

Not specified

Bachelor DegreeEnglishAirflowCloudETLKubernetesPythonSQL

Job Description

• Own and operate machine learning models that run in production, including monitoring, debugging, and iterative improvement. • Develop, train, and optimize models used in a real-time or near-real-time bidding and decisioning system. • Work with stakeholders to clarify ambiguous problems, define success metrics, and translate business needs into technical solutions. • Design and implement feature engineering pipelines, balancing model performance, latency, and maintainability. • Write production-quality Python code (not just notebooks) and collaborate with engineering on deployment, CI/CD, and system design. • Analyze model behavior using logs, metrics, and offline analysis to identify performance issues and opportunities. • Contribute to data pipelines and infrastructure where needed (e.g., ETL, materialized tables, model inputs). • Make thoughtful tradeoffs between something that is “theoretically optimal” and something that is reliable, fast, and shippable.

Job Requirements

  • Strong Python experience, including writing code that runs in production systems.
  • Solid SQL skills and experience working with analytical databases (Snowflake or similar).
  • Hands-on experience training and tuning tree-based models (e.g., LightGBM, XGBoost, CatBoost) on real, messy data.
  • Experience deploying, maintaining, or owning ML models beyond experimentation (APIs, batch jobs, or streaming systems).
  • Comfort working across dev, staging, and production environments.
  • Ability to operate with limited guidance: you can ask good questions, propose solutions, and move work forward independently.
  • Bonus Skills
  • Experience at a smaller company or on a small team where you wore multiple hats.
  • Depth in one or more of:
  • Gradient boosted models and performance optimization
  • Feature engineering for tabular data
  • Data engineering / ETL design
  • Model monitoring, evaluation, and debugging in production
  • Experience improving model latency, reliability, or cost—not just accuracy.
  • Prior technical leadership or informal mentoring experience.
  • Familiarity with Airflow, Kubernetes, or cloud infrastructure.

Benefits

  • Opportunity to work from home
  • Excellent work environment
  • Medical, dental, and vision insurance
  • Up to 15 days of paid time off
  • 11 company observed holidays
  • 8 weeks of paid parental leave
  • 401k plan with company match
  • Life insurance
  • Professional growth opportunity
  • Most importantly, an inclusive company culture established by an incredible team!

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