DTCC - Lead Data Scientist - Artificial Intelligence/Machine Learning

About the job

Are you ready to make an impact at DTCC?

Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We're committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.

The Information Technology group delivers secure, reliable technology solutions that enable DTCC to be the trusted infrastructure of the global capital markets. The team delivers high-quality information through activities that include development of essential, building infrastructure capabilities to meet client needs and implementing data standards and governance.

Pay And Benefits

- Competitive compensation, including base pay and annual incentive.

- Comprehensive health and life insurance and well-being benefits, based on location.

- Pension / Retirement benefits

- Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.

- DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee).

The Impact You Will Have In This Role

You will design, develop, and deploy Artificial Intelligence systems that solve complex problems and drive our technological advancement.

Your Primary Responsibilities

Generative AI Application Development:

- Design and implement AI solutions such as Retrieval-Augmented Generation (RAG) and Agentic AI Workflows using advanced techniques in prompt engineering and fine-tuning of Large Language Models (LLMs) and frameworks such as LangGraph.

- Conduct thorough evaluations of LLMs to ensure the models meet the desired performance criteria and are aligned with business goals.

- Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows, enhancing overall efficiency and capabilities.

- Develop robust evaluation metrics and benchmarks.

- Identify and address potential biases and limitations in LLMs.

- Develop and refine agentic workflows to empower AI systems to autonomously complete tasks.

- Design and develop machine learning models and algorithms to address business challenges and improve product features.

- Deploy machine learning models in production environments to ensure scalability and efficiency.

- Design, develop, and refine complex AI models, including traditional machine learning and generative AI models algorithms to address business challenges and improve product features.

- Deploy machine learning models in production environments to ensure scalability and efficiency.

- Optimize and refine models based on performance metrics and feedback.

- Architect scalable and efficient AI systems, ensuring optimal performance and resource utilization.

- Stay up-to-date with the latest advancements in AI research and technology.

Model Development and Deployment:

- Design and develop machine learning models and algorithms to address business challenges and improve product features.

- Deploy machine learning models in production environments to ensure scalability and efficiency.

- Design, develop, and refine complex AI models, including traditional machine learning and generative AI models algorithms to address business challenges and improve product features.

- Deploy machine learning models in production environments to ensure scalability and efficiency.

- Optimize and refine models based on performance metrics and feedback.

- Architect scalable and efficient AI systems, ensuring optimal performance and resource utilization.

- Stay up-to-date with the latest advancements in AI research and technology.

NOTE: The Primary Responsibilities of this role are not limited to the details above.

Talents Needed For Success

- Bachelor's or Master's degree in computer science, Statistics, Data Science, or a related field. Ph.D. in a relevant field is a plus.

- 7+ years of experience in Machine Learning and Data Science.

- Strong understanding of statistical methods, data structures, and algorithms.

- Strong programming skills in Python; experience with Machine Learning libraries and Generative AI frameworks (e.g., Pandas, NumPy, Matplotlib, Seaborn, TensorFlow, PyTorch, scikit-learn, LangChain) and LLMs.

- Experience building Agentic AI applications using Langgraph or similar frameworks

- Experience developing and deploying AI solutions on AWS cloud platform. Additionally, experience on Snowflake Cortex is plus.

- Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.

- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for deploying AI solutions.

- Proven experience in developing and deploying machine learning models in a production environment.

- Experience working with large datasets and performing data analysis.

- Previous experience in a similar role or industry is preferred.

- Excellent communication and collaboration skills.

- Strong problem-solving skills and analytical thinking

- Passion for learning and staying up-to-date with the latest advancements in AI field