• Manage LLM production in AWS Bedrock and OpenAI, including deployment, scaling, monitoring, and cost optimization.
• Perform hands-on coding and development work.
• Mentor data scientists, review code, and enforce best practices.
• Translate business goals into model KPIs and measurable impact.
• Prioritize resources and plan data science roadmaps.
• Define strategy for analytics and data science initiatives.
• Collaborate with leadership and product teams on data-driven opportunities.
• Work with the team on end-to-end data science projects from design to deployment.
• Present insights to both technical and non-technical audiences.
• Drive innovation and process improvement through data science.
• Design and validate analytical models using diverse tools.
• Ensure compliance with data privacy, security, and ethical standards.
• Integrate LLM solutions into enterprise workflows with reliability and security.

WHAT YOU WILL BRING

• Bachelor’s, Master’s or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, Data Science, or a related quantitative field.
• 6+ years of experience in Data Science, Machine Learning, or advanced analytics, with a proven track record of successful project delivery and leadership.
• Expertise in statistical modeling, ML, deep learning, data/text mining, and Gen AI prompting.
• Proficient in Python and SQL; experienced with large-scale, real-time data.
• Skilled in AWS and MLOps tools for model deployment and monitoring.
• Proven experience building and deploying production-grade ML systems.
• Strong knowledge of data visualization tools and methods.
• Excellent critical thinking and creative problem-solving skills.
• Committed to ethical data science and data privacy regulations.

Other skills:

• Expertise in advanced NLP and text analytics, including entity recognition, event detection, and multilingual modeling.
• Experience with information retrieval and web data mining, leveraging large-scale scraping, search relevance, and vector databases.
• Familiarity with knowledge graphs and relationship modeling to enhance risk intelligence and entity linkage.
• Strong understanding of MLOps and scalable ML systems using tools like Airflow, Docker/Kubernetes, and Cloud ML platforms.
  • Proven leadership and communication skills, with the ability to mentor teams and translate analytical outputs into business insights.