Data Scientist (ML) – 3 to 5 years

Role Overview

This role requires a minimum of one year of professional experience and a robust foundation in scalable machine learning implementations. The successful candidate will play a pivotal role in designing and deploying sophisticated models and reusable ML frameworks that improve productivity and help drive strategic business initiatives.

What You Will Do

Design, build, and deploy reusable machine learning frameworks, design and develop scalable machine learning models and frameworks, and maintain working knowledge of model deployment works internally.

Why It Might Be a Fit

The role requires a highly analytical and driven Data Scientist to join the team, with a strong emphasis on production deployment and operationalization, and a deep conceptual and practical understanding of traditional machine learning algorithms, statistical modeling, linear algebra, and probability theory.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a closely related quantitative discipline.
• A minimum of 3 to 5 years of professional experience in a Data Scientist or ML Engineer capacity, with a track record of deploying machine learning algorithms and/or ML frameworks into production environments.
• Advanced proficiency in Python and SQL.
• Familiarity with model lifecycle management tools (e.g., MLflow), model deployment/serving fundamentals (e.g., Docker, MLflow serving), CI/CD for ML pipelines, and modern database architectures.
• Deep conceptual and practical understanding of traditional machine learning algorithms, statistical modeling, linear algebra, and probability theory
• Working knowledge of Java and experience with version control and CI/CD systems (Git).
• Experience building reusable, config-driven or plugin-based systems (as opposed to single-purpose models), with an eye toward adaptability across use cases.
• Exceptional analytical reasoning, with the ability to operate independently and navigate ambiguous data challenges.
• Outstanding written and verbal communication skills, tailored to diverse professional audiences.

Tagged as: Pipeline Management, Python, SQL