Quantitative Research Intern Jobs

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Applied Science team builds models and tools that solve Ramp’s most critical problems: from underwriting businesses to combatting fraud to making spend management smarter. We’re deeply embedded in the business and provide a quantitative foundation for decision making. As an Applied Science intern, you’ll be a fully integrated member of the team and own your project from start to finish. Working with engineers, product managers, and business stakeholders, you’ll translate complex business needs into scalable machine-learning-driven solutions. This is a chance to apply ML concretely, ship code, and create genuine value for Ramp and our customers. You will focus on exciting problems in areas like: credit, fraud, growth, or our core product. What You’ll Do End-to-End ML : own the model lifecycle from data exploration and feature engineering to training, benchmarking, deployment, and monitoring State-of-the-Art AI : leverage the latest Large Language Models (LLMs) to solve novel problems and create new product capabilities for our cust

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

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

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

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,

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: As an ML Infrastructure Engineer, you will play a pivotal role in building and optimizing the reliable, high-performance ML platform that powers recommendations on X. We're looking for exceptional engineers who are passionate about our mission and have a strong desire to make a meaningful impact. RESPONSIBILITIES: Designing, building, and scaling GPU compute infrastructure, training frameworks, and experimentation tools to enable rapid iteration on ML hypotheses Developing data pipelines and integrating large-scale data, training, and inference systems Collaborating with ML teams to productionize models and ensure seamless integration across the stack Ensuring scalability, reliability, and efficiency of large-scale machine learning systems Working across the full stack to solve complex problems independently Mentoring junior engineers and contributing to the growth of the team BASIC QUALIFICATIONS: Bachelor, Master, Post-graduate or PhD in computer science, machine learning, or other quantitative discipline; or equivalent work experience 2+ years of industry experience working with high traffic or large-scale production environments, distributed systems, GPU infr

Data Scientist The Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value . Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling . We understand our company’s goals and proactively inform their direction with data so that our product can help more teams do great things. As a Data Scientist at Asana, you’ll help us ask the right questions and answer them rigorously. You’ll work closely with our Pro duct and Business teams to understand their goals and proactively inform their direction with data. You’ll keep taking on new responsibilities as you grow—from defining core metrics to building machine learning models and keeping the data flowin g in our pipelines This role is based in our Warsaw office with an office-centric hybrid schedule . The standard in-office days are Monday, Tuesday, and Thursday . Most Asanas have the option to work from home on Wednesdays . Working from home on Fridays depends on the type of work you do, and your recruiter can share more about the in-office requirements . We offer a Contract of Employment (UoP) for our employees in Poland . What you’ll achieve Design and analyze experiments to measure the impact of new product features. Investigate high-level questions like “What are the collaborative patterns of the most successful teams using Asana?” Add new metrics and aggregations to our data warehouse to make new classes of questions answerable. Build models to predict the growth trajectory of different customer segments. Partner with cross-functional stakeholders across engineering, product management, and business teams to drive data-informed decision-making. About you Bachelor's Degree in Computer Science, Math, Statistics, Engineering, a related quantitative field, or equivale

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 special focus on Stripe’s security. Projects include, but are not limited to: Leverage internal telemetry and logs to understand and design secure and safe access controls to sensitive data; Develop methods to model, quantify, and ultimately de-risk security-related incidents on Stripe data, assets, and networks; Collaborate across the company with engineering, PMs, and others to better understand, measure, and ultimately detect various malicious attack vectors. You will act as a key strategic data partner to the Security organization at Stripe, and help craft, guide, and drive the strategy and tactics needed to help ensure Stripe keeps and maintains the highest level of safety and security for critical business assets and customer data. What you'll do Responsibilities Provide senior technical direction to data teams on horizontal technical areas, including detection, modeling, metrics, observability, etc. Assume hands-on leadership, especially when helping teams resolve complex problems through iterative execution. Identify broad company problems and opportunities that can be tackled through data science Work with relevant teams to design and build the quantitative outputs and artifacts that deliver outsized value to our users and our business. Provide data-driven guidance to cross-functional partners on strategy for tracking and p

The FP&A team at Zoox drives financial analysis of key strategic investments, maintains short and long term financial models, and develops reporting for both internal and external stakeholders. As a Financial Analyst supporting Commercial Operations, you will partner with key stakeholders across Operations, Go-to-Market, Data Science, and Software teams to manage revenue planning and reporting processes for Zoox’s rapidly growing Robotaxi business. You will manage short and long-term financial planning cycles and financial and operational metric reviews to ensure efficient resource allocation. This will require a deep understanding of Zoox’s ridehail operations and spend drivers, establishing strong working relationships with executives, managers, and individual contributors across multiple departments, and utilizing enterprise systems and tools to establish robust financial models and dashboards. The goal for this role is to drive decision-making through timely and actionable financial insights. In this role you will: Own and maintain long-range, annual, and mid-year financial models for demand, fleet allocation, gross bookings and TNC fees Develop city-level models for commercial operations and drive financial analysis for market expansion Partner with operations, manufacturing, regulatory, and data science teams to ensure consistent and industrialized data pipelines for financial analysis Analyze large financial datasets from Anaplan, SAP S4, Databricks, and other internal data systems to drive actionable insights Support implementation of systems required for commercial operations through design, build, testing, and cutover phases Qualifications BA/BS degree, preferably in a Finance, Accounting, Data Science or a quantitative field 4+ years experience in an FP&A or other analytical field 2+ years of direct experience building models, forecast input templates, dashboards, and business proces

The FP&A team at Zoox drives financial analysis of key strategic investments, maintains short and long term financial models, and develops reporting for both internal and external stakeholders. As a Financial Analyst supporting Production Manufacturing, you will partner with several Manufacturing groups, Supply Chain, and Accounting teams to drive financial planning and MEC activities. You will own critical manufacturing KPIs, including inventory, BOM, and open PO planning, manage monthly S&OP cycles and close activities related to product costing. This role requires a solid understanding of cost accounting systems and processes as well as financial planning and reporting in a manufacturing environment. You will leverage SAP, Anaplan, and other reporting systems to analyze large financial datasets and provide actionable insights that influence operational strategy and manufacturing efficiency. In this role you will: Own inventory, BOM, open PO, and other manufacturing KPI planning and reporting Support monthly S&OP and forecast variance reporting to Finance, Manufacturing, and Supply Chain leadership Manage close activities including accruals and allocations for product costing Analyze large financial datasets from Anaplan, SAP S4, SAP Ariba, and other internal data systems to drive actionable insights Support implementation of systems required for production manufacturing through design, build, testing, and cutover phases Qualifications BA/BS degree, preferably in a Finance, Accounting, Data Science or a quantitative field 4+ years experience in an FP&A or other analytical field 2+ years of direct experience building models, forecast input templates, dashboards, and business process development in a manufacturing environment Experience with product costing and financial analysis in a manufacturing environment Experience working directly with best-in-class planning and re

POSITION SUMMARY: Natera is hiring a Machine Learning Scientist to join our AI and computational biology team. This role develops and deploys deep learning models across digital pathology, genomics, transcriptomics, and cell-free DNA (cfDNA) modalities. You will build multimodal AI systems that integrate imaging, molecular, and clinical data, leveraging proprietary genomic and clinical datasets. You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed minimal residual disease (MRD) testing. PRIMARY RESPONSIBILITIES: Design, implement, and evaluate deep learning models across biomedical data modalities, including histopathology imaging, genomic sequencing, transcriptomics, and cfDNA features Develop multimodal AI architectures that integrate H&E whole-slide imaging data with molecular and clinical data sources Build scalable, production-quality machine learning workflows and pipelines using cloud infrastructure (AWS) Apply modern machine learning techniques including convolutional neural networks (CNNs), vision transformers (ViTs), sequence transformers, representation learning, and foundation model fine-tuning Collaborate across technical and clinical teams to translate machine learning prototypes into validated tools Analyze model outputs to generate reproducible biological and clinical insights Document pipelines thoroughly and communicate data-driven findings clearly to cross-functional stakeholders QUALIFICATIONS: PhD in Computer Science, Computational Biology, Biomedical Engineering, Bioinformatics, Statistics, or a related quantitative discipline with a focus on machine learning or AI Core experience developing machine learning models for biomedical applications, specifically in medical imaging, computational pathology, genomics, transcriptomics, multi-omics, or molecular diagnostics Hands-on expertise with PyTorch and

We deliver foundational systems that shape the future of how technology is used in a top performing quantitative equity fund that manages over $78+ billion USD in financial assets. This is a fantastic opportunity in the exciting intersection of finance and technology where investment decisions are made using technology. Quantitative equity funds use programmed investment strategies and as a result, our technology team is crucial to its success. The team is headquartered and deeply rooted in West Coast Vancouver. We place high value on maintaining an entrepreneurial spirit and creating a culture where each of us has opportunities to succeed. What You Will Do The technology infrastructure team plays an essential role through innovative technologies on our hybrid (on-premise and cloud based) platform: distributed computing, petabyte-scale data storage, containerization, non-traditional high-performance databases, process orchestration, monitoring, data visualization and DevOps. You own the entire technology infrastructure life cycle: Engineer and support software and systems infrastructure. Introduce new foundational technologies that advance our software engineering capabilities to the next level. Collaborate with our software development teams on support issues and improvements to our infrastructure tools, processes, and software. Act as a conduit between our application development teams, and IT, network security, and other stakeholders to align priorities and translate business requirements into technical designs. Improve systems infrastructure reliability. Gather and analyze metrics from operating systems and applications to assist in performance tuning, fault finding and business continuity planning. Design, plan and implement solutions in an entrepreneurial spirit. What You Bring Programming Knowledge – you have an undergraduate, graduate, or post-graduate degree in a computer-related field OR exceptional programming skills gain

Who we are Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung. Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts. Our 1,700 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients . What you will be doing As a Junior Software Engineer in our London office , your role will encompass: working on engineering projects together with senior team members training and certification to enhance your skills in software engineering, data science, and data architecture. Qualifications Necessary education and experience Education: A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field. Programming Proficiency: Strong programming skills in Python and a solid understanding of data structures and algorithms. Software Engineering Fundamentals: A demonstrable understanding of version control and repository tools (Git, CI/CD) and a commitment to writing clean, well-documented code. Data Skills: Experience with SQL for querying relational databases. Problem-Solving Skills: An analytical mindset with the ability to break down complex problems into manageable steps. Eagerness to Learn: A genuine passion for technology and a proactive attitude towards self-development and learning new skills, as demonstrated through projects or coursework. Communication & Collaboration: Strong verbal and written communication skills, with the ability to work effectively in a team environment and learn from senior members. Desirable experience Cloud & MLOps Exposure: Basic fam

Who we are Artefact is a leading global consulting firm dedicated to accelerating the adoption of data and AI. We work with a variety of businesses, from supermarket chains, to private equity firms and telecoms; including Nissan, L'Oréal, Carrefour, WHSmith, Orange, Beiersdorf, BNP Paribas, and Samsung. Our success stems from combining advanced data technologies, agile methods for quick delivery, and dedicated teams of data scientists, data engineers, business consultants, and data analysts. Our 1,800 employees operate in 25 countries (Americas, Europe, Asia, Middle East, India, Africa) and we partner with 1,000+ clients . What you will be doing As a Senior Data Scientist in our London office , your role will encompass: Designing and implementing advanced data science and machine learning solutions to solve complex business problems. Taking ownership of project streams, from defining technical deliverables and timelines to presenting updates to client steering committees. Supervising and mentoring team members on code, deployment, and best practices. Architecting and deploying robust, scalable solutions using modern cloud technologies and MLOps principles. Qualifications Necessary education and experience Education : A Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field. Project & Team Leadership : Demonstrable experience supervising team members, taking responsibility for project delivery, defining technical tasks, and presenting project updates to both internal and client stakeholders. Advanced Modelling : Proven ability to implement a range of complex models such as time-series forecasting, gradient boosting, clustering, NLP, and Bayesian inference. ML-Ops & Orchestration : Strong experience with MLOps tools for orchestration, experiment tracking, hyper-parameter tuning, and deploying automated model retraining pipelines. Programming & Data Engineering : Proficiency in objec

We are seeking a highly skilled and experienced Staff Data Scientist to join our team and play a pivotal role in developing and deploying cutting-edge autonomous driving technologies. As a Staff Data Scientist, you will be responsible for tackling complex data challenges, driving innovation in machine learning and statistical modeling, and contributing to the advancement of our self-driving systems. You will work closely with a team of talented engineers and researchers in a fast-paced, collaborative environment. In this role, you will: Analyze large-scale datasets from various sources, such as fleet and simulation data, to extract actionable insights. Develop and evaluate novel algorithms and methodologies for data processing, feature engineering, model training, and performance optimization. Evaluate and validate model performance through rigorous testing and analysis, ensuring the safety and reliability of our systems. Communicate complex technical findings and recommendations to both technical and non-technical audiences. Mentor and provide technical guidance to junior data scientists and engineers. Qualifications Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field with 8+ years of experience as a Data Scientist. Strong programming skills in Python, including experience with relevant libraries such as scikit-learn, and Pandas & SQL. Expertise in a wide range of machine learning techniques, including deep learning, reinforcement learning, and statistical modeling. Experience working with large-scale datasets and distributed computing platforms (e.g., Spark, Hadoop) with solid understanding of data processing, feature engineering, and data visualization techniques. Strong communication and presentation skills, with the ability to effectively convey technical information to diverse audiences. Bonus Qualifications Experienc