Staff Data Scientist

About the Company

Responsibilities

• ● Own the full machine learning lifecycle-from problem framing and data exploration to modeling, deployment, and monitoring-for mission-critical initiatives.
• ● Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.
• ● Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.
• ● Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.
• ● Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.
• ● Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.
• ● Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.

Requirements

• ● 5+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.
• ● Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.
• ● Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.
• ● Experience with distributed data processing and training, real-time inference, and ML Ops frameworks
• ● Prior experience mentoring other data scientists or acting as a tech lead.
• ● Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.
• ● Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).
• ● Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.
• ● Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.
• ● Excellent communication skills and the ability to influence both technical and non-technical stakeholders.
• ● Strong business acumen with the ability to align technical solutions with company goals.
• ● An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.
• ● Familiarity with MLOps tooling for monitoring, drift detection, retraining