You’ll be a great fit if you have...
5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes.
Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn).
Expertise in time-series forecasting, ideally Deep Learning based, preferably in demand prediction or related areas.
Feature engineering, feature importance testing, explainability based experience.
Master’s or PhD in Computer Science, Machine Learning, Statistics, Engineering or a relevant field.
Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment).
Excellent communication and collaboration skills.

Publications in top-tier, peer-reviewed ML/AI venues (e.g. ICLR, ICML, NIPS, etc.)
Experience applying ML in domains like finance, trading, revenue management etc.
Familiarity with cloud based solutions on GCP platform (e.g., Vertex AI, PubSub, Cloud Run Functions).
Strong data visualization and exploratory data analysis skills.
Familiarity with code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures.
Participation in competitive programming or data science challenges (e.g., Kaggle).
If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we’d love to hear from you.