Data Scientist II

Talent Space, Inc. is seeking a highly skilled professional to support AI/ML initiatives in a regulated environment. The role involves advancing targeting models and delivering scalable, production-ready solutions that drive business outcomes. The ideal candidate should possess strong technical expertise, hands-on model development experience, and the ability to work independently while collaborating with cross-functional teams.

Key Responsibilities

• Model Development & Optimization: Design, develop, and optimize machine learning models to enhance targeting accuracy and business performance. Apply advanced techniques to refine existing models and create new solutions.
• Feature Engineering & Data Preparation: Build scalable feature pipelines, transforming raw datasets into high-quality model inputs while ensuring data integrity.
• Production & Pipeline Scalability: Transition analytical models into robust, production-ready pipelines. Ensure code quality, documentation, and adherence to best practices. Support model deployment and performance improvements.
• Cross-Functional Collaboration & Insight Translation: Collaborate with data science, analytics, and business teams to translate business problems into technical solutions. Communicate methodologies and results to non-technical stakeholders.

Qualifications:

• • Master's or PhD in Data Science, Computer Science, Statistics, or a related field.
  • Minimum 5 years of experience in data science and machine learning model development.
  • Proven track record of taking models from ideation through production deployment.
  • Proficiency in Python, SQL, and AWS.
  • Expertise in Machine Learning and/or Deep Learning techniques.
  • Experience with large-scale, complex datasets in collaborative environments.
• • Hands-on experience with claims data or similarly complex datasets.
  • Understanding of data privacy, compliance, and governance requirements.
  • Experience with MLOps practices, including pipeline automation and monitoring. Experience within healthcare, pharmaceutical, or other highly regulated industries