Description

Build and deploy analytical models to solve complex business problems using structured and unstructured data.

Responsibilities

• Translate business requests into specific analytical questions and communicate outcomes to non-technical stakeholders.
• Select appropriate modeling techniques and technologies based on data limitations and business needs.
• Develop, validate, and deploy statistical and machine learning models within established framework guidelines.
• Compose technical documentation for risk management, technical reviews, and knowledge persistence.
• Collaborate with Data Engineering, IT, and governance teams to ensure solutions align with specifications and regulatory standards.

Required Skills

• 10 to 12 years of relevant experience, including 6+ years in data science, machine learning, or quantitative analytics.
• Proficiency in Python and experience with machine learning libraries.
• Hands-on experience building and validating models for Time series Forecasting, Classification, Segmentation, Fraud Detection, NLP, and Deep Learning.
• Experience querying and preprocessing structured, semi-structured, and unstructured data using SQL, HQL, or NoSQL.
• Strong ability to write transparent, well-documented, and commented code.
• Working knowledge of R, SAS, and Tableau.
• Experience handling various data formats including JSON, XML, delimited files, text documents, and images.

Preferred Skills

• Experience with Domino Data Lab or AWS SageMaker.

Key Skills

Education

Bachelor's degree