Converge Signals, FSI - Data Scientist_Products & Platforms

Deloitte • Jersey City, NJ

22d • $122,000 - $240,500

About The Position

The Innovation & Delivery Transformation team is building AI-native platforms and products and investing in capabilities for future growth. Deloitte’s Converge for FSI business combines a start-up environment with enterprise scale to develop data-driven financial services products.

As a Data Scientist on the Signals for FSI team, you will build and refine the analytical models and insights behind a flagship product. You will work hands-on with financial services data to develop trusted models, collaborating across data science, product, and financial services domain expertise. The role involves translating industry use cases into data requirements and model specifications, validating data and model quality, and communicating findings to product, sales, and client-facing teams. Initial use cases include retail banking, investment and wealth management, and insurance, with potential to expand over time.

The position is available in multiple U.S. locations and requires an average of 10–25% travel, depending on the work, clients, and industries served. Recruiting for this role ends on 12/1/2026. The estimated salary range is $122,000–$240,500. The role may also be eligible for a discretionary annual incentive. Candidates must be legally authorized to work in the United States without employer sponsorship now or in the future.

Requirements

• Bachelor’s degree in Computer Science, Statistics, Data Science, Mathematics, or a related quantitative field.
• At least 4 years of experience in applied data science, machine learning, or statistical modeling, including hands-on model development and validation.
• Proficiency using Python, SQL, and other data transformation and analytical tools.
• Ability to travel an average of 10–25%, depending on the work, clients, and industries or sectors served.
• Must be legally authorized to work in the United States without employer sponsorship now or at any time in the future.
• Genuine interest in and working knowledge of the financial services industry, with curiosity about how data translates into client outcomes.
• Strong analytical rigor and sound judgment about whether a signal or model is ready to ship or needs further refinement.
• Ability to move between hands-on technical work and clear communication with product, engineering, and business stakeholders.
• Self-directed and organized, with the ability to manage multiple analytical workstreams.
• Collaborative approach and willingness to partner closely with engineering and product teams.
• Comfort working through ambiguous, messy problems requiring creativity and persistence.

Nice To Haves

• Master’s degree in Computer Science, Statistics, Data Science, Mathematics, or a related field.
• At least 2 years of experience working with financial services data, such as banking, capital markets, investment management, or insurance, or delivering analytics solutions to financial services clients.
• At least 2 years of experience working with customer data to build audiences and segments for sales and marketing use cases.
• Experience with cloud-based data and analytics platforms such as Snowflake, Databricks, AWS, Google Cloud, or Azure in a financial services or other highly regulated industry context.
• Experience with MCP servers and using AI to analyze large datasets.

Responsibilities

• Develop, test, and refine statistical and machine learning models using financial services datasets, including consumer, business, transaction, account, risk, or market data.
• Partner with the Product team to translate financial services use cases into data requirements, features, data signals, and model specifications.
• Conduct exploratory data analysis and validate data quality across structured and semi-structured financial services data sources.
• Evaluate model performance against business and regulatory considerations relevant to financial services, and iterate based on findings.
• Translate analytical findings into clear, business-relevant insights for Product, Sales, and client-facing teams.
• Stay current on statistical and AI/ML techniques and financial services data trends, and evaluate their application to the Signals for FSI roadmap.
• Collaborate with engineering and product teams to bring models into production.

Benefits

• Broad range of employee benefits; specific benefits are not listed.
• Professional development opportunities, including on-the-job learning, formal development programs, mentorship, and leadership opportunities.
• Potential eligibility for a discretionary annual incentive program, subject to program rules and applicable performance factors.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior