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Analytics & Science Full-time · Remote / Hybrid

Data Scientist

Frame, build, and improve models that drive better decisions, automation, and business outcomes. Combine analytical rigor with experimentation, communication, and applied delivery.

Role Summary

We are hiring a Data Scientist to help identify, build, and improve models that drive better decisions, automation, and business outcomes. This role combines analytical rigor, model development, experimentation, and close collaboration with product, engineering, and domain stakeholders. The ideal candidate can move beyond notebook exploration to applied problem solving: framing use cases, selecting the right methods, evaluating impact, and working with teams to operationalize what works.

What You'll Do

Core Responsibilities

  • Frame analytical and predictive problems in business terms and translate them into workable modeling approaches.
  • Build, test, and improve statistical, machine learning, or decision models.
  • Evaluate models using metrics that reflect real business and workflow outcomes.
  • Explore data, engineer features, validate assumptions, and communicate findings clearly.
  • Support operationalization by working with engineering teams on deployment, monitoring, and iteration.

Strategic & Cross-Functional Responsibilities

  • Partner with product and business stakeholders to identify high-value use cases.
  • Help define experimentation strategies, success metrics, and learning plans.
  • Contribute to reusable modeling approaches, evaluation patterns, and feature logic.
  • Surface data quality, labeling, and workflow issues that affect model performance.
  • Support responsible and explainable model use in business settings.

What You Bring

Required Qualifications

  • 3+ years of experience in data science, machine learning, advanced analytics, or related fields.
  • Strong Python, SQL, and statistical reasoning skills.
  • Experience building and evaluating predictive or analytical models on real-world data.
  • Ability to communicate results clearly to technical and non-technical audiences.
  • Strong problem-solving skills and comfort with ambiguity.

Preferred Qualifications

  • Experience in experimentation, forecasting, optimization, or classification/regression use cases.
  • Familiarity with productionization patterns, model monitoring, or MLOps workflows.
  • Experience in consulting, product, or client-facing environments.
  • Exposure to LLM or generative AI use cases is a plus.
  • Experience working closely with data engineering or product teams.

Skills and Capabilities

Technical Skills

Exploratory analysis and feature engineeringStatistical testing, validation, and experimental designModel evaluation, error analysis, and business-impact interpretationReproducible analytical workflowsCollaboration with engineering for deployment and monitoring

Domain & Business Skills

Framing business problems into solvable analytical questionsBalancing model performance with explainability and usabilityUnderstanding decision workflows and operational constraintsTranslating findings into recommendations and next stepsBuilding trust through clear reasoning and evidence

Tools, Platforms, and Languages

Python, SQL, notebooksML libraries and analytical toolkitsVisualization and communication toolsCloud or warehouse-based analytical environmentsExperiment tracking or model lifecycle tools

What Success Looks Like

  • Models and analyses improve actual business decisions or workflows.
  • Findings are understandable, credible, and actionable.
  • Modeling work moves into production or durable operational use where appropriate.
  • Teams learn faster through structured experimentation and evaluation.
  • Reusable methods and insights accumulate across projects.

How You'll Collaborate

Internal Partners

AI Engineers, Data Engineers, Product Managers, Analysts, Strategists

Client Partners

Business stakeholders, subject matter experts, operations leaders, functional teams

We are committed to creating an inclusive workplace and providing equal opportunity to all applicants and employees. We welcome candidates from all backgrounds and provide reasonable accommodations throughout the hiring process.