Job Description

The impact you will have in this role:

Being a member of the Technology Research and Innovation team, you will help advance DTCC's ability to explore, validate, and productize emerging data science, machine learning, AI, and GenAI capabilities that create measurable value across the organization. This role sits at the intersection of research, applied machine learning, data engineering, and product development, with a strong focus on moving ideas beyond experimentation into scalable, production-ready solutions. The Principal Data Scientist / Machine Learning Engineer will design and deliver practical, production-oriented solutions in a financial services environment where governance, risk, controls, reliability, and business adoption are critical. This is not a purely theoretical research role; the ideal candidate will have demonstrated experience taking data science, machine learning, AI, or GenAI concepts from ideation through prototype, validation, productization, and deployment while partnering closely with product owners, technology teams, business stakeholders, and innovation leaders to rapidly develop solutions, test feasibility, define a path to production, and align technical work to real business outcomes.

Your Primary Responsibilities:

• Champion Python-Centric Data Engineering: Spearhead the adoption and optimization of Python for data engineering tasks, including data ingestion, transformation, and advanced analytics. Guide team in leveraging Python libraries and frameworks to build scalable, maintainable solutions
• Architect Data Pipeline Solutions: Strategically design and implement enterprise-grade data pipelines for optimal data processing thru python and Snowflake. Establish standards for data quality, security, and integrity, and ensure seamless integration of disparate data sources and formats
• Strategic Cross-Functional Collaboration: Partner with technology teams to identify opportunities for leveraging data and analytics. Translate business requirements into technical solutions and ensure that insights are actionable and aligned with organizational objectives
• Lead Advanced Machine Learning Initiatives: Direct the design, development, and deployment of robust machine learning models using Python, guiding teams in data preprocessing, feature engineering, model optimization, and evaluation. Oversee the application of advanced techniques, including deep learning, regression, classification, and clustering, to solve high-impact business problems
• Demonstrate accountability by taking ownership of solution ideation, development, and execution, including coordinating efforts with internal and external teams/stakeholders to present the results (reports and presentations) in a clear and concise manner
• Technical Leadership and Mentorship: Provide guidance and technical leadership to junior engineers, create high-performance and reusable approaches to solve challenging problems, and cultivate a culture of excellence, continuous learning, and innovation
• Risk Management and Compliance: Integrate risk and control processes into all data engineering activities, proactively monitor for potential issues, and escalate risks as appropriate to ensure compliance with organizational standards

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

Qualifications:

• Minimum 8 years of related experience
• Bachelor's degree (preferred) or equivalent experience

Talents Needed for Success:

• Extensive experience in data engineering and machine learning model development using Python
• Proven expertise in architecting data pipelines with Python and Snowflake
• Strong leadership and mentorship skills, with experience managing and developing technical teams
• Excellent communication and collaboration abilities
• Sound understanding of data governance and risk management
• Experience in Financial industry is preferred
• Experience in Data Visualization tools is a plus