Junior Data Scientist

You’ll dive into diverse datasets—finance, healthcare, retail, and beyond—to uncover patterns that shape strategy. Expect to write clean code, build and test predictive models, and translate results into crisp visuals that anyone can grasp. Our mentors pair with you on every sprint, ensuring steady growth as you refine statistical thinking and model-centric programming.

What You’ll Do  

- Explore structured and unstructured data, validating quality and filling gaps.  

- Prototype machine-learning pipelines (classification, regression, clustering) in Python or R.  

- Tune models with cross-validation, hyper-parameter searches, and feature engineering.  

- Craft dashboards and storyboards in Tableau or Power BI that spotlight actionable insights.  

- Document experiments—assumptions, metrics, surprises—to create a reusable knowledge base.  

- Present findings to stakeholders through concise slide decks and live demos.  

- Partner with DevOps to containerize models using Docker and deploy via REST APIs.  

- Support ongoing AI initiatives by troubleshooting data flows and monitoring model drift.  

Must-Have Skills  

- Bachelor’s degree in Computer Science, Statistics, Mathematics, or related discipline.  

- Solid grasp of Python (pandas, NumPy, scikit-learn) and SQL for analytical queries.  

- Working knowledge of TensorFlow or PyTorch for deep-learning experiments.  

- Ability to visualize data with Matplotlib, Seaborn, or similar tools.  

- Analytical mindset, problem-solving drive, and clear written communication.  

- Eligibility to work in the United States.  

Nice-to-Have Extras  

- Experience with cloud services (AWS SageMaker, Azure ML, or GCP Vertex AI).  

- Familiarity with Git workflows and CI/CD pipelines.  

- Exposure to big-data frameworks such as Spark or Databricks.  

- Competition participation (Kaggle, DrivenData) demonstrating end-to-end projects.