Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

About the Role:

We are seeking a detail-oriented Contract Technical Writer to spearhead a critical documentation overhaul for our Account Risk and Transaction Risk teams. This role is not just about recording processes; it is about building a foundation for the future of our operations. You will be responsible for auditing existing procedures, bridging documentation gaps, and—most importantly—structuring our Standard Operating Procedures (SOPs) for ingestion by LLMs and other AI tools.

What You Will Do:

• SOP Modernization: Audit and update legacy SOPs for the Account Risk and Transaction Risk teams to ensure they reflect current platform tools, compliance standards, and operational workflows.
• Documentation Gap Analysis: Partner with leaders across risk to identify areas where processes are undocumented or rely on "tribal knowledge," and shadow SMEs to draft new, comprehensive SOPs from scratch.
• AI Optimization & Structuring: Re-engineer documentation into high-quality, structured formats (such as Markdown) optimized for RAG (Retrieval-Augmented Generation) and LLM ingestion.
• Information Architecture: Apply consistent metadata, hierarchical tagging, and clear taxonomies to ensure that an AI can accurately parse, index, and retrieve risk-related information.
• Cross-Functional Collaboration: Partner with Risk Leads, Product Managers, and Engineering teams to ensure that documentation evolves in lockstep with product updates and fraud-prevention strategies
• Quality Control: Maintain a high bar for clarity, brevity, and actionable instructions, ensuring all content is accessible for both human analysts and automated systems.

What We Look For:

• Experience: 3+ years of experience in technical writing, preferably within FinTech, Risk Operations, Trust & Safety, or highly regulated environments.
• Risk Knowledge: A fundamental understanding of risk monitoring, fraud detection, or transaction dispute processes.
• AI Fluency: Familiarity with how LLMs process information and a proven ability to structure content for "Chat-with-your-docs" internal tools.
• Technical Proficiency: Strong skills in Markdown, Confluence, Git, or similar documentation-as-code tools.
• SME Engagement: A natural ability to interview technical experts and translate complex, high-stakes processes into simple, foolproof instructions.
• Detail Obsession: You are someone who catches the smallest inconsistency and understands that in Risk, the details are everything.

This is a temporary contract position with an expected duration of three months, with the potential for extension if needed.

New Hire Hourly Pay Rate: $60/hr. - $65/hr.

At Bluevine, we recognize the importance of fair and competitive compensation. Exact compensation may vary based on a variety of factors, including your experience, skills, and qualifications, as well as market trends.

The Impact You’ll Make: 

Recursion is currently seeking a seasoned leader to join our team as Vice President, Real World Experience. This role will lead RWE generation across the Recursion portfolio. The role will be responsible for building a world-class team of statisticians, pharmacoepidemiologists, and statistical programmers. This VP and their team will partner closely with the biometrics team, clinical development, and other internal stakeholders. The role will involve, but will not be limited to, supporting study planning, generating natural history data to contextualize rare disease trials, contributing to health authority interactions, supporting value demonstration for submission to HTA bodies, and other evidence-generation needs. 

We are looking for someone who is innovative and can build systems, programs, and teams from the ground up. 

In this role, you will: 

• Build, develop, and lead our RWE team
• Participate in governance meetings and provide strategic and scientific input
• Build a roadmap for real-world data licensing and prioritization 
• Strategic and scientific contribution to interventional study design and planning
• Conduct externally controlled studies where appropriate and relevant
• Natural history data generation to support study planning and contextualize observed efficacy in rare disease programs
• Support external stakeholder engagement, such as regulatory agencies and HTAs 
• Build academic partnerships 

The Experience You’ll Need: 

• 12+ years of relevant experience in biotechnology or pharmaceuticals 
• Strong background in causal inference in non-randomized settings 
• Strong background in machine learning
• Familiarity with at least one statistical programming language such as SAS, R, Python, or others. 
• Knowledge of the regulatory landscape for rare diseases and oncology. 
• Knowledge of regulatory guidance on the use of RWE.
• Knowledge of the global reimbursement landscape and the use of RWE for reimbursement  support
• Bonus points for familiarity with CDISC standards 
• Strong written and oral communication skills 
• Ability to travel as needed to our various office locations; up to 25%
• Bachelor’s in a quantitative field; Masters or PhD in a quantitative field preferred

Working Location & Compensation:

This is an office-based, hybrid position at our US headquarters located in Salt Lake City, Utah, or our office in New York City, New York. Employees are expected to work in the office at least 50% of the time.

At Recursion, we believe that every employee should be compensated fairly. Based on the skill and level of experience required for this role, the estimated current annual base range for this role is $319,000 to $437,800 (USD). You will also be eligible for an annual bonus and equity compensation, as well as a comprehensive benefits package. 

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