Junior Data Scientist

An innovation lab funded by a Fortune 500 parent tackles high-volume, high-variety datasets across finance, healthcare, retail, and media. Small cross-functional squads iterate quickly, deliver measurable value, and celebrate experimentation.

What you’ll do  

- Explore structured and unstructured data, profile quality, and surface anomalies that influence model outcomes.  

- Clean and transform datasets using Pandas, PySpark, and SQL, ensuring reproducible pipelines.  

- Build and validate regression, classification, and clustering models with scikit-learn, TensorFlow, or similar frameworks.  

- Visualize insights through Tableau, Matplotlib, or Seaborn dashboards, guiding non-technical stakeholders.  

- Craft concise technical documentation and present findings in sprint reviews.  

- Partner with product managers, software engineers, and UX researchers to embed models in production APIs.  

- Contribute to automated tests, monitor drift, and tune models for accuracy and fairness.  

- Participate in weekly knowledge-sharing sessions—spark discussion, ask sharp questions, propose bold ideas.

Your toolkit  

- Bachelor’s degree in Data Science, Computer Science, Statistics, or a related STEM field.  

- 0-2 years’ hands-on experience—or equivalent academic projects—using Python for data manipulation.  

- Working knowledge of SQL joins, window functions, indexing, and query optimization.  

- Familiarity with statistical concepts: hypothesis testing, A/B design, confidence intervals.  

- Exposure to machine-learning workflows: feature engineering, cross-validation, hyperparameter tuning.  

- Proficiency with at least one visualization platform (Tableau, Power BI, or matplotlib).  

- Git literacy plus comfort with Linux command line.  

- Clear written and verbal communication; you translate numeric evidence into plain English.  

- Adaptable mindset, receptive to feedback, eager to iterate fast.  

- US work authorization and availability to collaborate across Eastern and Central time zones.

Why this team  

- Remote flexibility—work from any US location with reliable internet.  

- Dedicated mentor tracks your first twelve months and maps growth objectives.  

- Quarterly innovation days let you prototype passion projects that may ship to production.  

- Blended agile process balances research depth with shipping cadence—no endless slide decks.