Senior Data Scientist

TIFIN•Charlotte, NC

7d•$150,000 - $190,000

About The Position

TIFIN builds the AI operating layer for wealth. Our platform delivers agentic workflows across the industry’s core personas—investors, advisors, investment teams, and operations—so financial institutions can move faster, serve more clients, and deliver better outcomes with the same (or fewer) resources. We combine finance-native AI, specialized data, and enterprise-grade controls to deploy secure, compliant capabilities into real production environments. As a Senior Data Scientist, you will build and deploy the ML growth engine behind TIFIN AMP — a production machine learning platform driving acquisition, expansion, retention, and distribution intelligence across wealth enterprises and asset managers. This is an individual contributor role with close collaboration with engineering and customer success.

Requirements

4+ years shipping production ML systems
Strong supervised learning experience
Experience modeling consumer behavior, flows, or lifecycle dynamics
Python, SQL, DBT
AWS or Snowflake experience
Bias toward shipping measurable impact

Nice To Haves

Client Retention & Churn Prevention: Build early-warning models that detect signals of potential client attrition, allowing advisors to proactively intervene.
Asset Consolidation: Develop predictive models that identify clients most likely to consolidate additional assets with the firm, enabling advisors to proactively deepen relationships and increase assets under management.
Cross-Sell & Wallet Share Growth: Design models that identify the highest-propensity opportunities for additional products and services within existing client relationships.
Advisor & Prospect Prioritization: Create scoring frameworks that rank advisors and prospects by growth potential, enabling sales teams to focus on the most impactful opportunities.
Product–Advisor Matching: Develop models that predict product–advisor fit and likelihood of engagement, improving targeting and accelerating product adoption.

Responsibilities

Build and deploy the ML growth engine behind TIFIN AMP
Drive acquisition, expansion, retention, and distribution intelligence across wealth enterprises and asset managers
Own the full ML lifecycle: EDA → feature engineering → training → validation → deployment → monitoring
Own end to end model implementation for one or more enterprise clients
Engineer large-scale feature pipelines across AUM, transactions, CRM, and third-party datasets
Deploy models using AWS (SageMaker, Redshift, S3) and/or Snowflake
Design A/B tests and control frameworks to measure lift in inflows and conversion
Translate model outputs into clear, actionable intelligence used daily by advisors and wholesalers