Data Analyst Jobs

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,

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B

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: The Cyber Security team at Freddie Mac is searching for a strong data analyst to collaborate on developing and administering data security policies as well as safeguarding information, evaluating existing data security procedures and identifying new areas of risk for Freddie Mac. If this role sounds like a fit for your skill set, please read on, apply and learn why there is #MoreatFreddieMac ! Our Impact: We develop and train the enterprise on relevant Identity and Access Management best practices, develop and support automated IAM processes, and develop and implement ongoing IAM efficiency improvements with limited oversight by managers. The role will work closely with Enterprise partners and security control owners on IAM automation development activities and alignment of IAM processes with InfoSec maturity targets as described in the InfoSec Strategy. Your Impact: Senior Data Analyst who can develop and implement new and updated business process automation for all Identity and Access Management activities. Develop and proposes strategies to reduce security risk in the organization by implementing procedural prevention, detection, and response measures, while still enabling positive business outcomes. Comfortable supporting ad hoc data retrieval and analysis requests using SQL queries and Copilot/Excel . Creating audit-ready reference documentation. This role will allow for and support rapid AI-based extrapolation/replication of these services as future automated IAM microservices. Qualifications: Typically, 5 - 7 years of rel

About StarRez StarRez is the global leader in student housing software, providing innovative solutions for on and off-campus housing management, resident wellness and experience, and revenue generation. Trusted by 1,400+ clients across 25+ countries, StarRez supports more than 4 million beds annually with its user-friendly, all-in-one platform, delivering seamless experiences for students and administrators. With offices in the United States, Australia, the UK, and India, StarRez blends the robust capabilities of a global organization with the personalized care and service of a trusted partner. The Role You have an uncanny knack for problem solving and you have a sharp product mindset. Our engineers are involved in all aspects of the software design process and create high-performing, scalable, and secure products. You’ll work alongside cross-functional teams to design right-size solutions that power a new market-leading Analytics platform. As a Data Engineer at StarRez, you will play a critical role in building and scaling the foundations of our Analytics & Data Platform. You’ll design and maintain reliable, secure, and scalable data pipelines and models that power a new generation of reporting, insights, and data-driven products across the StarRez ecosystem. This role sits at the intersection of data, product, and engineering. You will work closely with Data Analysts, Full-Stack Engineers, and Product teams to translate customer and business requirements into robust data solutions - enabling everything from standardised dashboards to advanced analytics and embedded intelligence. You are hands-on, pragmatic, and comfortable working in a fast-evolving environment where you’ll help shape both the technical platform and the operating model as we scale. What you’ll be doing Build and maintain scalable data pipelines to ingest, transform,

Role Overview You’ll help global clients keep their most critical corporate governance data accurate, secure, and easy to use. As a Professional Services Data Entry Specialist, you turn complex client records into clean, reliable datasets and documents that board members, legal, risk, and compliance teams rely on to make decisions. In this role, you’ll work hands-on with governance data, migrate it between platforms, build smart questionnaires for directors and officers, and use Excel, databases, and AI tools to streamline how information is captured and maintained. You’ll collaborate closely with clients and internal teams, spot data issues early, and suggest better ways of working so implementations run smoothly and clients are set up for long-term success. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Migrate and transform client corporate governance data and documents into Diligent platforms, ensuring accuracy, consistency, and completeness. Build and configure Director & Officer questionnaires so clients can collect the right information from the right stakeholders. Run regular data quality checks, validate data against source records, and quickly correct errors to maintain high data integrity. Use advanced Excel functions, databases, and AI tools to manage, format, and optimize large data sets and bulk document uploads/downloads. Partner directly with client stakeholders and internal teams to clarify requirements, resolve data or technical issues, and provide clear progress updates. Identify and help implement improvements to data workflows, templates, and automation to make delivery faster, more consistent, and more scalable. These are the essentials you’ll need to get an interview Hands-on experience in a data-focused role (for example, data specialist, data analyst, data migration, or similar) in a professional environment. Strong skills in Microsoft Excel, including advanced functions for manipulating and analyzing data

Job title: Data Validation Role Purpose (overall high level summary of the role) Finance has mobilised the first phase of a five year programme to transform the Finance operating model by leveraging cloud technology. Finance Cloud Transformation will rationalise operational processes, automate data and report production, to deliver comprehensive data to our internal and external stakeholders for analysis and reporting. The programme will entail migration of core Finance data and processes to the cloud, with an initial phase to implement a standard global operating process for Finance actuals report production, followed closely by forecast data and report production. The vision for the Finance on the Cloud Programme is “to deliver standardised global processes that leverage a single dataset for reporting, analysis and forecasting.” Key programme outcomes are to deliver a singular automated data production processing capability for actuals and forecasting, correction of data once for all downstream calculations, reports and outputs, introducing automated preventative and detective controls, significantly reduce manual activity in the run-time actuals process to allow the production of all actuals outputs by working day 5 for a monthly process The Data Analyst will be expected to support the delivery of data related activities within the FotC programme. Various aspects may include data validation, solution functionality validation, data gap analysis, reconciliation, user tooling or automation testing activities. • The role holder will be responsible to functionally understand and test our liquidity core release requirements • He/ She is required to perform a detailed data validation to ensure the data reflects accurately across all liquidity returns for all applicable regulations - PRA/EBA/HKMA/US FED etc. • He/She needs to furnish UAT dashboards and walkthrough the Reporting Ops of the changes introduced by liquidity core release requirements • He/She is

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An Overview of This Role GitLab is seeking a VP of Data and Insights to lead the strategic vision, architecture, and execution of our enterprise data platform and analytics capabilities. Reporting to the CIO, you'll oversee a distributed team spanning data platform and engineering, analytics engineering, data governance, and data analysts embedded across business functions. This role represents a transformational opportunity to move GitLab beyond traditional dashboard development toward a truly AI-enabled, self-service data organization where stakeholders access insights on demand and data analysts focus on high-value strategic w

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 The Data Science and Analytics organization at Stripe partners with teams across the company to drive rigorous, data-informed decision-making at scale. Within this org, the Verifications and Greater China data teams deliver critical analytical and data science work—from identity verification and risk modeling to market-specific growth insights—that directly shapes Stripe's ability to serve users safely and expand into new markets. Today, the team comprises individual contributors distributed across Singapore and India, supporting two high-impact pillars. We're looking for a founding Data Science Manager based in Bengaluru to build and lead this growing regional footprint from the ground up. What you'll do This is a rare 0 → 1 leadership role with a dual mandate. Pillar 1—Direct Team Leadership • Manage a team of Data Scientists and Data Analysts (currently 4 individual contributors across India and Singapore) spanning the Verifications and Greater China workstreams. • Own roadmap prioritization, execution quality, and stakeholder alignment for both workstreams. • Drive hiring for open and future roles in India, building a high-caliber data team in a competitive talent market. • Foster individual contributor growth through real-time coaching, mentorship, career development, and performance management. Pillar 2—Regional Data Craft Lead (India Office) • Serve as the founding data craft leader for Stripe's India office. Set quality standards, es

Senior Data Scientist Description - Job Summary • This role is responsible for enabling innovation and creativity by bringing cutting edge perspectives on adopting latest data mining and modelling techniques. The role understands current complex business problems and future business strategy to assess, build and deploy required data mining and modelling capabilities. The role is involved in driving standardization, productivity and cross team learning by establishing processes and SOPs for entire data model development lifecycle. The role drives excellence through continuous improvement in model accuracy and reliability. Responsibilities • Leads organization wide team or teams of other data science professionals in complex projects to mine data using modern tools and programming languages. • Defines models to uncover patterns and predictions creating business value and innovation. • Manages and creates relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives. • Ties insights into effective visualizations communicating business value and innovation potential. • Works with various stakeholders, including business leaders, engineers, product managers, and data analysts, to identify business problems and develop data-driven solutions. • Prepares and presents literature, presentations, invention disclosures for peer review & publication in industry data science domain initiatives and conferences. • Assures insights are communicated regularly and effectively, reviewing designs, models and data compliance. • Defines, communicates and drives data insights/innovation into the business. • Leverages recognized domain expertise, business acumen, and overall data systems leadership to influence decisions of executive business

About THG Ingenuity THG Ingenuity is a fully integrated digital commerce ecosystem, designed to power brands without limits. Our global end-to-end tech platform is comprised of three products: THG Commerce, THG Studios, THG Fulfilment. Each represents a single, unified solution, overcoming challenges and taking brands direct-to-consumer. Our client portfolio includes globally recognised brands such as Coca-Cola, Nestle, Elemis, Homebase, and Proctor & Gamble. What’s the role? Job Title: CX Apprentice - Data Reports to: CX Analytics and Performance Director Apprenticeship: Data Analyst Level 4 Duration: 12-18 months, subject to learner progress + End Point Assessment Role Purpose To support the Customer Service department in turning core operational data into clear, actionable insight — covering everything from divisional headcount and budgets through to CS performance metrics, carrier claims and returns — helping the business understand performance and identify where the customer experience can be improved. Key Responsibilities Support core CS operational performance reporting across the department, including divisional headcount, budgets and key performance metrics such as CSAT and APH. Collect, clean and validate data from multiple internal and external sources across CX/CS operations, including carrier claims, returns (e.g. ZigZag), post-dispatch communications and customer contact systems. Build and maintain dashboards and reports (e.g. Power BI) tracking department-wide CS metrics, from workforce and budget data to claims and returns performance. Write and run SQL queries to extract and manipulate data from relational databases in support of departmental reporting. Identify trends and patterns across headcount, budget, claims, returns and delivery data, flagging root causes and opportunities for improvement. Support CS leadership and wider teams with ad hoc analysis to inform decision-making, resourcing

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to car

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to carve out the ownershi

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 Our Product Marketing team's mission is to generate customer insights that inform Stripe's product strategy, and lead go-to-market for our suite of products. Product Marketing is a highly cross-functional role at Stripe, partnering closely with Product and Engineering, Sales, Partnerships, Demand Generation and Campaigns to name a few. Different from many other Product Marketing teams, our team works across the entire product lifecycle, from helping shape the product, to driving launch and commercialization, to growing product adoption post-launch. We are looking to hire a Product Marketing Manager to own go-to-market strategy and drive adoption for Stripe's data products — including Sigma, Data Pipeline, Database, and new products we’re incubating. As monetization grows more complex — from AI companies hyperscaling globally to enterprises integrating Stripe deeply into their operations — data has become a critical lever that helps businesses make better decisions. What you'll do As a key owner of our GTM strategy for Stripe's data products, you'll need to quickly build a deep understanding of our products, the data analytics buyer, and our competitive differentiation. You will: Be the expert on our data analytics buyers — understand how data analysts, analytics engineers, and BI practitioners evaluate and adopt tools, and translate those insights into product roadmap recommendations and GTM strategy. Own positioning and messaging for Stripe's data

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