Quantitative Analytics Professional Jobs

Markets Quantitative Analyst - Capital Analytics — New York New York United States. Apply via Workday.

Markets Quantitative Analyst - Capital Analytics, AVP — London United Kingdom. Apply via Workday.

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb, a leader in travel and hospitality, is on a mission to create a world where anyone can belong anywhere. We offer unique accommodations and experiences, crafted and curated by locals. As we expand into new marketplaces for in-person experiences and services, we are on the lookout for driven and innovative individuals to help shape our growth trajectory. The Difference You Will Make: Airbnb is seeking a Staff, Advanced Analytics, to support our Guest App team. This individual will act as a senior thought partner, supporting strategic business and product initiatives through detailed data analysis, experimentation, statistical modeling, and the development of reporting tools and metrics. The individual will be instrumental in driving product decisions for the Guest App, especially for strategically important Promotional Merchandising initiatives, to optimize for the company's objectives and ensure optimal experiences for guests. A Typical Day: Be the Advanced Analytics owner and expert on domain datasets. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches. Apply technical expertise with quantitative analysis, experimentation, data mining, forecasting and the presentation of data to identify trends and patterns that can inform decision-making. Collaborate closely with Product, Engineering, Finance, Marketing, Operations, Data Science, Advanced Analytics, Data and Analytical Engineering, and other cross-functional teams to provide actionable insights. Design, execute, and analyze experime

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: We are currently seeking a Quantitative Risk Analysis Manager to join the Credit Analytics & Reporting team in the Single-Family division. This position will be tasked with managing a team responsible for reporting and analytics regarding Collateral offerings as well as Collateral model business user supports. The role requires deep understanding of data and current code base, designing analytical approaches for business questions and scenario evaluations, managing data research, analyses and preparation of reports and presentations. Our Impact: Our team is responsible for producing reporting packages to monitor trends and performance. We analyze different test and learn or pilot programs to assess risk of the offerings and create reports to monitor these offerings closely to assess broad roll out. We perform significant user activities for enterprise Collateral models for user acceptance testing and provide feedback. Your Impact: Manage a team of three to four people Complete baseline processes and reports monthly and interpret results as it relates to collateral risk management Follow appropriate controls and standards established to maintain and document for processes & reports. Participate in performing ad-hoc analytics in support of collateral policy Cleanse, manipulate and analyze large datasets using statistical software Collaborate with team members and interact across organizational lines to meet business objectives Qualifications: Degree in

We are looking for a Data Analyst to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-tuned machine responsible for generating key decisions that drive trades and investment insights. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in data. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of data, investment, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data analytics and data science skillsets to enable the Quantitative Equity Team’s research. Your role will involve identifying and assessing brand new data, data exploration, and proposing robust ways to integrate data products from many sources. You will be supported with coaching and mentorship from senior members of the team, and we will create the conditions for you to

We are looking for a Data Scientist to join our Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We are dedicated to the mission-critical operation of our investment engine—a well-oiled machine responsible for generating key investment insights that drive trades. Leveraging data analytics, finance knowledge and cutting-edge technology, we aim to ensure that new and useful data products are continuously ready for research. Do you love the idea of evaluating and integrating large proprietary data sources into valuable applications? Are you a wizard at transforming ‘messy reality’ into high quality data assets? As a core member of our team, you will collaborate with investment and data experts to tackle challenging problems, and to continuously expand our capabilities in the data space. Based on the west coast in Vancouver, we value mentorship, collaboration, and growth in a supportive and innovative environment. Join us to make a significant impact on our investment outcomes and overall success. What You Will Do This is an exciting full-time role for individuals who are enthusiastic about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management and our investment process. You will then continue to a specialized role utilizing data science, machine learning, AI, and process engineering skillsets to accelerate the Quantitative Equity Team’s data preparation and modelling functions. Your specialized role will involve building, scaling, managing and evaluating our integrated data model, in direct support of alpha research. You will be supported with coaching and mentorsh

Roles & Responsibilities Displays structured problem solving, application of right tools & techniques to solve open ended problems, Creates productized analytics solutions or frameworks independently. Understand Business & product problems and come up with deep data backed solutions. Root cause analysis and Deep dive analysis of certain product problems Running and maintaining the reporting system, presenting insights at a weekly forum Building templates, dashboards in Power BI, Gsheets for operational and management reporting Data extraction as per business request for Ad hoc analysis Business analysis and understanding Evaluating metrics to be tracked as per business goals, exploring other available metrics for deeper understanding of product performance Work in a fast-moving environment, across multiple projects with varying levels of complexity and detailing Desired Skills and Experience: 3 - 5 years working with large data sets and conducting quantitative analysis Some understanding of Statistics and prior experience of building statistical models (e.g. hypothesis testing, product experimentation, A/B Testing, regressions). Excellent knowledge SQL and intermediate knowledge of data manipulation language such as R/Python Previous experience with working on ecommerce funnels, retention Ability to think through product and business metrics to assess product features Knowledge of business modelling and basic knowledge of financial metrics, would be a bonus Quick learner and ability to work in dynamic work environment Team player and comfortable interacting with people from multiple disciplines Established expertise in designing new dashboards, identifying the right metrics, layout; displays proficiency in building dashboards on Power BI using best practices and intuitive Qualifications Bachelor’s in engineering, Computer Science, Economics, Statistics, or related discipline from a reputed institute ...........................

Opportunity Overview: We are seeking a Healthcare Analytics Analyst to join our Analytics team. In this role, you will conduct analyses that drive our strategy, inform product performance, and provide insights critical to the development of new clinical intervention strategies and product enhancements. You'll partner closely with cross-functional teams and clients to optimize auto-decisioning performance and deliver increased value. This is an opportunity to directly impact company growth and assist patients at a critical time in their healthcare journey. What you'll do: Research, build, execute and optimize auto-decisioning strategy for new client implementations Work with multiple types of healthcare data to build and maintain analytical and reporting solutions to support strategy and program decision making Identify optimization opportunities based on analyses to improve auto-decisioning performance and drive increased value for clients Perform quantitative analysis of health care cost, operational performance and clinical outcomes using claims and authorization data Track cost, utilization and industry trends to inform stakeholders of solution performance and provide insights around opportunities to optimize clinical value for patients, providers and payers Prepare information for clients, build reports, data visualization and self-service solutions for internal and external stakeholders Develop, review, and analyze detailed data sets leveraged for client reporting/analytics Collaborate with IPA team on rule refinement and metric tracking What you'll need: Must-haves 2-5 years in an analyst role, ideally at a health tech company, health plan, or healthcare consulting firm Has worked hands-on with claims data, authorization data, or utilization management data Proficient in SQL (daily use) Has built and maintained dashboards in Tableau or PowerBI for internal and external stakeholders Bachelor's degree in Health Informatics, Public Health, Data Analytics, o

Role Description At Dropbox, people are our greatest asset. The People Analytics team partners closely with leaders across the company to help them make better, data-informed decisions about how we identify, attract, develop, and retain top talent. As Dropbox continues to scale and evolve its Talent Acquisition strategy, we’re looking for a Data Analyst who is passionate about problem-solving and using data to shape how we hire. In this role, you’ll partner deeply with Talent Acquisition, People Partners, and business leaders to analyze hiring data, uncover trends, and surface insights that influence workforce planning, recruiting strategy, and candidate experience. You’ll work across quantitative and qualitative data to understand what drives successful hiring outcomes, where bottlenecks exist, and how we can improve efficiency, quality, and equity in our hiring processes. You should have a demonstrated ability to think analytically about the business, translate ambiguous questions into structured analyses, and deliver clear, actionable insights. Success in this role requires strong attention to detail, high standards for data quality, and the ability to communicate findings in ways that drive real decisions. Responsibilities Partner on analytics initiatives to understand and improve the effectiveness, efficiency, and quality of hiring across Dropbox. Create clarity from ambiguity, bringing structure to complex data and stakeholder narratives to identify the underlying question, establish analytical rigor, and drive actionable conclusions. Monitor and analyze core Talent Acquisition metrics, proactively identifying trends and uncovering the “what” and “why” behind changes in performance. Build strong relationships with key stakeholders; lead requirements gathering and translate business questions into clear analyses and insights that inform People and business leader decisions. Answer complex business questions through independent investigation and data forensics,

Role Description At Dropbox, people are our greatest asset. The People Analytics team partners closely with leaders across the company to help them make better, data-informed decisions about how we identify, attract, develop, and retain top talent. As Dropbox continues to scale and evolve its Talent Acquisition strategy, we’re looking for a Data Analyst who is passionate about problem-solving and using data to shape how we hire. In this role, you’ll partner deeply with Talent Acquisition, People Partners, and business leaders to analyze hiring data, uncover trends, and surface insights that influence workforce planning, recruiting strategy, and candidate experience. You’ll work across quantitative and qualitative data to understand what drives successful hiring outcomes, where bottlenecks exist, and how we can improve efficiency, quality, and equity in our hiring processes. You should have a demonstrated ability to think analytically about the business, translate ambiguous questions into structured analyses, and deliver clear, actionable insights. Success in this role requires strong attention to detail, high standards for data quality, and the ability to communicate findings in ways that drive real decisions. Responsibilities Partner on analytics initiatives to understand and improve the effectiveness, efficiency, and quality of hiring across Dropbox. Create clarity from ambiguity, bringing structure to complex data and stakeholder narratives to identify the underlying question, establish analytical rigor, and drive actionable conclusions. Monitor and analyze core Talent Acquisition metrics, proactively identifying trends and uncovering the “what” and “why” behind changes in performance. Build strong relationships with key stakeholders; lead requirements gathering and translate business questions into clear analyses and insights that inform People and business leader decisions. Answer complex business questions through independent investigation and data forensics,

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: We are looking for an expert leader to join our community as the Staff Payments Advanced Analytics. In this capacity, you will be a vital driver in executing the strategic vision for Airbnb's global Payments operations. As a key data thought partner, you will streamline integrated, data-informed decision-making across the Payments Platform, Product, and Operations teams. Our organization is dedicated to achieving operational excellence and enhancing the Guest and Host experience through a rigorous culture of problem-solving fueled by data and research. You will embed quantitative measurement into our user journeys and product processes, establishing objective indicators for success. Collaborating with a cross-functional team of engineers and finance partners, you will oversee the technical details of fund processing, including collection, reconciliation, and settlement systems. Your expertise in building relationships and framing narratives will be essential as you influence stakeholders at every level to drive global process improvements and optimize our payments data landscape. The Difference You Will Make: Act as a vital data thought partner to leadership, delivering actionable insights and recommendations that empower integrated, data-informed decision-making across the organization. Champion day-to-day analytics while architecting scalable reporting platforms to enhance the efficacy of our payments ecosystem. Pinpoint frictions in the user journey to optimize experiences for our global Guest, Host, and agent communities through rigorous problem-solving. Solve complex domain cha

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices: New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role: We are looking for Associate Manager Analytics who will work on a broad range of data analytics, data visualization and business intelligence problems across a variety of industries. More specifically, you will: • Engage with clients to understand their business context • Understand business processes and map the complete process in visual formats. • Translate business problems into analytical structures and solve using statistical/ML techniques • Manage a team of data analysts to deliver solutions for clients. • Collaborate with a team of data scientists and engineers to embed AI and analytics into the business decision processes. Desired Skills & Competencies: • Developing and enhancing algorithms and models to solve business problem. • Providing end-to-end analysis support across different industry domains and application areas. • Generate data cuts/outputs according to agreed specifications (for example, survey data clean up, weighting data, recoding variables, creating custom tabular views, and running cross-tabulations) • Conducting quantitative analyses and interpreting results • Proficient in visualisation tools such as Power BI, Tableau, QlikView, Spotfire (Any). • Proficient in MS SQL Data

Citi's Markets Quantitative Analysis (MQA) group is seeking a highly skilled VP Quantitative Analyst to join its Equities team. This role is central to the research, design, implementation, and maintenance of cutting-edge Equities Execution Algorithms for Citi's clients and internal trading desks, with a specific focus on North America and LATAM markets. This position offers a unique opportunity to apply strong quantitative, technical, and soft skills to foster innovation within a collaborative team culture, directly impacting trading businesses, control functions, and the global client base. Key Responsibilities Algorithmic Development & Enhancement: Design and develop new algorithms and strategies for the next generation equity trading platform initiative at Citi. Research, design, and implement improvements for existing algorithmic trading strategies (e.g., VWAP, liquidity seeking). Develop and enhance quantitative models, including optimal schedule, market impact models, and short-term predictive signals (e.g., fair value). Implement algorithm enhancements and customizations with production-quality code, applying best practices for modular, reusable, and robust trading components. Data Analysis & Modeling: Perform in-depth analysis of large datasets comprising market data, orders, executions, and derived analytics. Apply statistical modeling and machine learning techniques for data analysis and signal generation. Conduct flow analysis and performance tuning for various client flows. Provide data and analysis to support initial model validation and ongoing performance analysis. Collaboration & Support: Collaborate closely with traders, risk managers, product, sales, and technology teams to integrate quantita

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

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.” As a Data Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward. Responsibilities Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals Develop frameworks and scalable processes to drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience Monitor and diagnose KPI performance and present findings to senior leadership Experience Degree in a quantitative field like statisti