Company: BespokeLabs (VC-backed; founded by IIT & Ivy League alumni)
Type: Contract | Remote
Compensation:$25$40/hour (open to reconsideration for exceptional talent)
About BespokeLabs
BespokeLabs is a venture-backed startup specializing in AI-driven systems and next-gen digital products. Founded by seasoned IIT and Ivy League alumni, our mission is to harness advanced machine learning to solve real-world problems with speed, precision, and scale.
Role Overview
We are seeking a highly skilled Senior Data Scientist with strong end-to-end ownership of ML projects, exceptional analytical ability, and hands-on experience building and deploying production-grade models.
Responsibilities
- Design, develop, and deploy machine learning and statistical models.
- Conduct data exploration, feature engineering, and hypothesis testing.
- Build scalable pipelines for model training, evaluation, and inference.
- Perform rigorous model evaluations and optimize for accuracy, performance, and stability.
- Collaborate with engineers to integrate models into production systems.
- Research and apply state-of-the-art ML and deep learning techniques.
- Communicate insights clearly to both technical and business stakeholders.
Requirements
- 5+ years of Data Science with real-world, production use cases.
- Strong proficiency in Python, machine learning algorithms, statistics, and model evaluation.
- Experience with ML libraries/frameworks: scikit-learn, TensorFlow, PyTorch, etc.
- Ability to manage full ML lifecycle: data prep modeling deployment monitoring.
- Strong understanding of data structures, algorithms, and applied math fundamentals.
- Experience with cloud platforms (AWS/GCP/Azure) is a plus.
- Familiarity with MLOps tools (Airflow, MLflow, Docker, etc.) is beneficial.
- Kaggle competition experience or strong Kaggle profile is a significant plus.
Why Join Us
- Work on challenging, high-impact AI problems.
- Be part of a high-talent, fast-moving, zero-bureaucracy team.
- Flexible remote contract role with competitive pay.
- Opportunity to grow into a long-term role based on performance.
