Quantitative Insurance Solutions Analyst Jobs

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. About Enterprise Risk & Internal Audit The Enterprise Risk & Internal Audit department protects Affirm’s operations and long-term success. We identify, assess, and monitor risk across the business. Our work includes internal audits, regulatory assurance, fraud prevention, and crisis planning. The team maintains strong controls, tracks key risk indicators, and ensures readiness for external reviews. We uphold accountability, transparency, and resilience to support responsible growth. About the Team We're looking for a sharp, driven quantitative professional to join our dynamic Model Risk Management (MRM) team. In this role, you will oversee the underwriting and credit risk validation sector - the most critical pillar of Affirm’s MRM framework. This is a unique position designed for a seasoned technical leader who can build, mentor, and manage a high-performing team while remaining deeply hands-on, personally executing validations of our most complex machine learning models. You'll collaborate across the company to shape a best-in-class risk framework, ensuring our models are robust, reliable, and ready for the future. If you're passionate about the intersection of finance, credit risk, and data science, this role is for you. What You'll Do: Sector Leadership & Team Management: Oversee the underwriting and credit risk validation sector. Lead, mentor, and manage a team of talented quantitative professionals while setting the strategic direction for this critical risk domain. Hands-On Model Validation: Execute rigorous, independent validations of sophisticated machine learning models across underwriting and credit risk management. Technical Review: Evaluate conceptual soundness, data integrity, and performance stability through comprehensive testing, in-depth reviews, and continuous

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. Social Finance, LLC seeks Software Engineer, Account Linking in San Francisco, CA: Job Duties: Own and ideate on technical solutions for product requirements and user stories with minimal supervision. Participating heavily in code and design reviews. Delivering resilient and scalable code. Communicate engineering concepts and efforts with outside stakeholders in product marketing, operations, business, legal, and compliance. Work in a fast-moving, highly collaborative environment across multiple offices. Use different object-oriented programming languages to build performant and scalable applications in a cloud-based microservice architecture. Participate in shaping the technical architecture of the product. Generate ideas for new initiatives and technologies. Part-time telecommuting is an option. Hybrid work from Social Finance offices in San Francisco, CA. Requirements: Master’s degree in Computer Science, Engineering (any field) or related quantitative discipline and (2) two years of experience in the job offered or in a related occupation. Special Skill Requirements: (1.) Modern object oriented programming language (2 yrs); (2.) REST APIs; (3.) Relational Databases; (4.) SQL and NoSQL Database; (5.) Microservices; (6.) Java or Kotlin (1 yr); (7.) Spring Boot; (8) Docker; (9) Kafka and (10.) React. Any s

ROLE/RESPONSIBILTIES: We are seeking a NLP engineer for a NLP research team within Point72. The ideal candidate has a track record of developing modern NLP solutions, including the use of LLMs, agents, RAG, open-source models fine-tuning and deployment, etc. Responsibilities include: Exploring and combining rich internal and external textual datasets Building GenAI solutions, leveraging both internal models and external APIs Formulating research hypothesis to derive alpha Post-training models for specific tasks Benchmarking LLM approaches internal tasks We believe the investment world offers unique opportunities to use modern NLP methods. We are a team ideally situated for that, having access to both internal and commercial datasets, with an end-to-end research philosophy and direct portfolio impact. REQUIREMENTS: Bachelor, Master’s or PhD graduate or candidate in computer science or another quantitative discipline Experience in NLP, particularly LLMs. Proficient in Python, SQL and general software engineering principles (github, testing, etc.) Data science stack familiarity Interest in financial markets Collaborative mindset ABOUT POINT72: Point72 is a leading global alternative investment firm led by Steven A. Cohen. Building on more than 30 years of investing experience, Point72 seeks to deliver superior returns for its investors through fundamental and systematic investing strategies across asset classes and geographies. We aim to attract and retain the industry’s brightest talent by cultivating an investor-led culture and committing to our people’s long-term growth.

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Single-Family Data Analyst At Freddie Mac, you will do important work to build a better housing finance system, and you’ll be part of a team helping to make homeownership and rental housing more accessible and affordable across the nation. We are accepting applications for this position until 10/16/2026 Position Overview: The Single-Family division within Freddie Mac is searching for creative individuals to join our organization. This role is ideal for candidates with a strong foundation in statistical analysis, quantitative problem solving, and data-driven decision making. Successful candidates will demonstrate curiosity, strong communication skills, and an eagerness to learn how emerging technologies, including AI-enabled tools, can enhance business outcomes. Our Single-Family College Analyst Cohort program is crafted to ease the transition of college into the workforce by providing skills training and mentorship programs, as well as in-class learning opportunities with senior leadership. Our Impact: Single-Family relies on data analysis, quantitative modeling, and emerging technologies to support business decisions, risk management, and operational effectiveness. We provide data governance capabilities that help teams find, understand, and use data effectively across product, project, and delivery efforts. We support credit risk strategy, policy implementation, performance monitoring, and loan lifecycle analysis through data-driven insights. Your Impact: Document well written User Stories based on communication, discus

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview Multifamily Capital Markets is seeking an exceptionally curious, analytical, and driven professional to help identify, prioritize, and deliver the initiatives that can most improve the business. This is a rare opportunity to develop a broad view across the Multifamily Capital Markets organization, including loan pricing, pipeline risk management, portfolio management, securitization, credit-risk transfer, operations, and technology. You will work directly with a Capital Markets leader who brings deep Multifamily expertise, extensive Wall Street markets and product experience, and a track record of developing innovative solutions to complex financial problems. Together, you will examine how the business operates, identify its highest-impact opportunities, challenge existing assumptions, and develop solutions from first principles. This is a hands-on role combining original problem-solving, quantitative analysis, and end-to-end initiative delivery. You will research unfamiliar topics; analyze financial, market, and operational data; build analytical models and lightweight Python prototypes; test hypotheses; frame business questions; and develop fact-based recommendations. You will write the memos and presentations that move decisions forward, document conclusions and requirements, coordinate contributors, maintain project plans and follow-ups, and drive multiple initiatives through organizational and technical roadblocks from initial idea through implementation. This role is designed for someone who enjoys learning unfamiliar topics, solving difficult problems, and taking ownership of outco

About the Role OpenAI’s Industrial Compute organization is responsible for ensuring our compute infrastructure scales efficiently to support millions of users and increasingly sophisticated AI models. We’re looking for a Data Scientist to partner closely with Capacity Systems Engineering, Infrastructure, Product, and Research to optimize inference capacity across our global GPU fleet. This role combines statistical modeling, large-scale data analysis, forecasting, and systems thinking to drive critical decisions around infrastructure investments, performance-efficiency trade-offs, and customer experience. You’ll transform complex operational data into actionable insights that directly influence how OpenAI allocates and scales one of the world’s largest AI compute environments. Key Responsibilities Build statistical and machine learning models to profile and improve GPU utilization, latency, throughput, and overall fleet efficiency. Develop forecasting models for inference demand across products, regions, and model families. Analyze production workloads to identify latency bottlenecks and capacity constraints, highlighting optimization opportunities. Partner with Capacity Systems Engineering to inform infrastructure planning and long-term GPU investment strategies. Design experiments and simulations to evaluate scheduling policies, serving strategies, and infrastructure tradeoffs. Build dashboards and operational metrics that enable leadership to make data-driven capacity decisions. Collaborate with Product, Research, Finance, and Infrastructure teams to align compute planning with business growth and model roadmaps. Communicate technical findings clearly to both engineering teams and executive leadership. Qualifications MS or PhD in Statistics, Computer Science, Operations Research, Applied Mathematics, Economics, or related quantitative discipline (or equivalent industry experience). 5+ years of experience working in the infrastructure data science space. Strong ex

Role: VPN Engineer Location: Gurgaon Graviton is a privately funded quantitative trading firm striving for excellence in financial markets' research. We are seeking a Network Engineer for our team in Gurgaon. Graviton trades across a multitude of asset classes and trading venues using a gamut of concepts and techniques ranging from time series analysis, filtering, classification, stochastic models, pattern recognition to statistical inference analysing terabytes of data to come up with ideas to identify pricing anomalies in financial markets. Responsibilities Manage and support corporate network infrastructure across multiple locations, including routers, firewalls, switches, wireless access points, VPN gateways, Internet links, and LAN/WAN connectivity. Configure and troubleshoot VPN technologies such as IPsec, SSL VPN, site-to-site VPN, remote-access VPN, WireGuard, OpenVPN, and FortiClient/FortiGate VPN, including issues related to authentication, tunnels, routing, DNS, packet loss, performance, split tunnelling, and firewall policies. Manage secure connectivity between offices, data centres, cloud environments, and remote users. Configure and maintain office LAN infrastructure, including VLANs, trunk/access ports, inter-VLAN routing, DHCP, DNS, NAT, ACLs, static routing, BGP, and OSPF where required. Manage multiple ISP connections, including primary and backup Internet links, automatic failover, and monitoring of utilization, latency, jitter, packet loss, and link availability. Coordinate with ISPs and telecom providers for new circuits, link failures, bandwidth upgrades, routing issues, packet-loss investigations, and service escalations. Manage firewall policies, NAT rules, VPN policies, network objects, and routing, while regularly reviewing and removing unnecessary access. Implement network segmentation across user, server, management, guest, and other business networks, while maintaining secure administrative access to network equip

At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview Multifamily Capital Markets is seeking an exceptionally curious, analytical, and driven professional to help identify, prioritize, and deliver the initiatives that can most improve the business. This is a rare opportunity to develop a broad view across the Multifamily Capital Markets organization, including loan pricing, pipeline risk management, portfolio management, securitization, credit-risk transfer, operations, and technology. You will work directly with a Capital Markets leader who brings deep Multifamily expertise, extensive Wall Street markets and product experience, and a track record of developing innovative solutions to complex financial problems. Together, you will examine how the business operates, identify its highest-impact opportunities, challenge existing assumptions, and develop solutions from first principles. This is a hands-on role combining original problem-solving, quantitative analysis, and end-to-end initiative delivery. You will research unfamiliar topics; analyze financial, market, and operational data; build analytical models and lightweight Python prototypes; test hypotheses; frame business questions; and develop fact-based recommendations. You will write the memos and presentations that move decisions forward, document conclusions and requirements, coordinate contributors, maintain project plans and follow-ups, and drive multiple initiatives through organizational and technical roadblocks from initial idea through implementation. The successful candidate will be expected to operate with substantial independence and combine analytical depth with exceptio

About Bolna Bolna is Voice AI infrastructure built for India - and now for the world. We help businesses deploy intelligent voice agents that can call, converse, and convert in any language, at scale. From collections to customer support to sales, our agents handle millions of conversations so humans don’t have to. We’re a YC F25 company, backed by General Catalyst, with 1,050+ paying customers and growing fast. Our team of ~25 is based in Bengaluru. The Role Every voice AI agent Bolna deploys makes real-time judgment calls - when to speak, when to go silent, when a customer is done talking, when to hand off. We’re building automated systems to grade these calls at scale, using LLMs as judges of call quality. But before you trust a model’s judgment, you verify it against a human’s. That’s this role. You’ll listen to real calls, annotate what actually happened, and check whether our automated systems - LLM-as-judge evals and quantitative signal detection - got it right. It’s precise, high-attention work, and it sits right at the center of how we know our voice agents are actually working. This is an internship role for someone early in their career who wants hands-on exposure to how a voice AI company builds trust in its own AI. What You’ll Do Annotation Listen to and annotate real customer calls - transcription review, issue tagging, labeling - using tools like Label Studio Follow (and help sharpen) annotation guidelines for a multilingual environment (Hindi, English, Hinglish, ) Verifying LLM-as-Judge Evaluations For calls flagged by our automated eval pipeline, verify whether the model’s call was actually correct - for example, confirming whether a detected barge-in (agent/customer talking over each other) genuinely happened by listening to the audio Mark agreements and disagreements clearly, with reasoning, so we can measure and improve model accuracy over time All tools needed for this will be provided Verifying Quantitative Measures Check system-flagged quantit

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Team The Financial Modeling Team is a part of the Customer & Product Support (C&PS) department which sits at the intersection of sales, customer success and technical support. The Financial Modeling team is comprised of finance professionals with prior experience in investment banking, equity research, and holds at least one of the following qualifications: Chartered Financial Analyst (CFA), Certified Financial Planner (CFP) or Certified Management Accountants (CMA), Financial Risk Manager (FRM). The team aims to understand our users' financial data needs to provide solutions that enhance M&A and quantitative research workflows. The Financial Modeling team provides expert services for our analytical tools so that we can provide customers with a tailored experience when using our products. This seasoned team of investment professiona

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. SoFi Bank N.A. seeks Staff Data Scientist in San Francisco, CA: Job Duties: Identify opportunities and collaborate cross functionally to develop, implement, and continuously improve machine learning models and strategies that support credit underwriting. Identify opportunities to apply AI and advanced machine learning approaches to solve complex business problems. Evaluate alternative data sources and external vendor solutions by defining and driving proof of concept projects to demonstrate the solutions business values. Explore and leverage inhouse, external, and other opensource machine learning software/algorithms. Contribute in enhancing SoFi’s risk model development code base by developing customized Python scripts or packages. Collaborate with Model Risk Management team and Fair Lending team to demonstrate models are developed with high level rigor that satisfy Model Risk Management requirements, Fair Lending requirements, and other regulatory requirements. Spearhead model deployment by collaborating with cross functional teams including Credit, Product, Engineering, and Business Unit. Present model performance and insights to Credit, Risk, and Business Unit leaders. Full-time telecommuting is an option. Requirements: Master’s degree in Statistics, Data Science, or a related quantitative discipl

Datadog’s Product Analytics suite spans Product Analytics, Session Replay, Feature Flags, and Experimentation. Together they give product teams a complete, quantitative and qualitative picture of how users experience their applications, plus the tools to release, measure, and improve those experiences with confidence. Our team of Applied Scientists makes this space smarter and more autonomous, researching, prototyping, and industrializing AI/ML capabilities that make the suite proactive and agentic by default: AI-driven event understanding and instrumentation, conversational analytics, automated insight reporting, and UI/UX issue detection from session replays. The ambition is to let product teams act with autonomy, moving from question to insight to safely released change without depending on engineering or analysts. As the Engineering Manager for this team, you’ll lead a team of Applied Scientists through an early-stage, high-impact opportunity: defining the team’s technical vision, growing its footprint, and shaping how AI capabilities get built and delivered across the suite. This is greenfield work, both in the R&D itself and in the team you’ll grow around it. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead and grow a team of Applied Scientists researching, prototyping, and industrializing AI/ML capabilities across the suite Define the technical vision and roadmap for the suite’s agentic and proactive AI/ML capabilities: event understanding, conversational analytics, insight reporting, and session-replay issue detection Stay hands-on as a technical contributor and reviewer, helping the team move from research prototypes to production-grade capabilities Shape how AI capabilities get built and delivered across the suite, partnering closely wi

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role SoFi is seeking a Fraud Model Developer to join our Fraud Model Development team. In this role, you will develop, evaluate, and monitor machine learning models that support data-driven fraud and risk decisions across SoFi’s products and services, including Personal Loans, Student Loans, Credit Cards, and Crypto. You will build quantitative and machine learning solutions designed to reduce fraud losses, minimize false positives, lower operational costs, and protect SoFi members. You will also analyze model and product performance, identify key drivers of fraud losses, and translate complex findings into actionable recommendations for business and risk partners. This role requires strong experience in machine learning, statistical modeling, data analysis, and model performance monitoring. You will work closely with Fraud Risk, Fraud Operations, Product, Engineering, Finance, Accounting, and other business teams to develop scalable fraud-modeling solutions and ensure model performance and loss trends are clearly communicated. What you’ll do Develop quantitative, statistical, and machine learning models that reduce fraud losses, minimize false positives, and lower operational expenses associated with fraud complaints and disputes. Aggregate, clean, and synthesize large datasets from multiple data envir

Chicago Trading Company (CTC) is a premier proprietary trading firm specializing in options market making. Our collaborative culture fuels innovation in quantitative research, systematic trading strategies, and cutting-edge trading technology. For over three decades CTC has provided critical liquidity across derivatives exchanges worldwide - making them fairer, more transparent, and more efficient. We strive to be the most innovative firm in the industry today, tomorrow, and long into the future while upholding ethical excellence. We believe that CTC makes a positive impact on the markets, the lives of our employees, and all the communities to which we belong. Started in 1995 by a team of forward-thinking Traders, we are proud to call ourselves an industry leader that keeps making markets and each other better. Are you excited by the opportunity to be part of a dynamic trading environment that values teamwork and collaboration? Do you thrive in an innovative atmosphere? If so, we encourage you to consider Chicago Trading Company! The Role The Quant Trading Associate (QTA) role is our entry-level position within our Trading and Quant organization and gives you broad exposure to the whole business as you work towards graduating from the Associate Program and assuming a role as a Quant Trader or Quant Researcher. As a QTA, you will work in a high-impact role as a member of a trading or quantitative team. You will play a vital part in identifying trading opportunities and impacting your team through dynamic problem solving — including trade execution, strategy formulation, back-testing, data analysis, and the modeling and pricing of traded financial derivatives — while communicating with traders, risk managers, software engineers, and quants throughout the trading day. You will learn all aspects of the trading and quant operation and work towards a role that generates trading revenue or drives strategy development for the team. In addition to the

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team You’ll be joining the data science team at Stripe responsible for our overall infrastructure, with a focus on core systems and cloud platforms. Projects include, but are not limited to: Developing models to predict resource needs as Stripe demand increases; Working closely with engineers to improve the cost and performance of platforms and services; Employing quantitative methods to drive and automate fleet decisions. You will act as a key strategic data partner to the Core Infrastructure organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe can continue to scale with efficiency and dependability as our business rapidly grows. What you'll do As a Data Scientist, your role will involve: Analyzing infrastructure usage, efficiency, and workloads to predict demand and inform capacity planning. Developing models and strategies for efficient compute resource consumption and provisioning. Collaborating with engineers, engineering leadership, and finance teams to ensure Stripe makes the right, data-driven, infrastructure decisions. Providing actionable insights and recommendations to improve infrastructure operations to reduce costs and improve reliability. Utilizing your analytical expertise to influence both technical and financial strategies within Stripe. Who you are We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements,