Junior Applied Scientist

You join a multidisciplinary research squad that ships real-world AI solutions for finance, healthcare, gaming, retail, and government projects. Expect to blend coding, statistics, and critical thinking as you translate business questions into deployable models.

What You’ll Do

- Write clean, testable Python to build and refine machine learning pipelines.  

- Analyze structured and unstructured data - discover patterns, validate hypotheses, visualize insights.  

- Debug training bottlenecks, profile performance, and fine-tune hyperparameters.  

- Document experiments, metrics, and findings in reproducible notebooks.  

- Maintain and version datasets with modern MLOps tools (DVC, Weights & Biases, MLflow).  

- Collaborate with senior scientists, data engineers, and product managers to deliver end-to-end solutions.  

- Proactively optimize models for speed, fairness, and interpretability.  

- Contribute to literature reviews and support publication of internal research notes.  

What You Bring

- Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or related STEM field.  

- 0–2 years of hands-on experience with Python and popular AI libraries (PyTorch, TensorFlow, scikit-learn).  

- Solid grasp of supervised and unsupervised learning, experimental design, and applied statistics.  

- Familiarity with SQL, Pandas, and data visualization frameworks such as Matplotlib or Seaborn.  

- Comfort using Git, CLI tools, and Linux environments.  

- Strong problem-solving instincts, logical reasoning, and an eye for reproducibility.  

- Clear written and verbal communication - you explain complex ideas in plain English.  

- Adaptability to shifting priorities, you thrive in a fast iteration loop.