Data And Monetization Analyst Jobs

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping work on top priorities for the company. The Data team also functions as an in-house, production "customer" that dog foods Databricks and drives the future direction of the products. The impact you will have: “ Analysis at the speed of thought ”: Inform decision making by building robust data science tooling for business leaders, analysts, and other data scientists. “ Extend capabilities of Databricks ”: Work closely with Data Platform and Product Engineering teams to integrate data science tooling with existing Data team offerings and the core product “ Strategic bus

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We o ff er 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 a Senior Data Analyst 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 Database. Python knowledge is good to have. Strong analytical and problem-solving skills. Storyboarding, Client Interaction is a value addition. Education & Desired

P-57 At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best Data Intelligence Platform, so our customers can focus on the high value challenges that are central to their own missions. Founded in 2013 by the original creators of Apache Spark, Databricks has grown from a tiny corner office in Berkeley, California to a global organization with over 1000 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest growing SaaS companies in the world. Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security and scale that is critical to making customers successful on our platform. We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we regularly observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above. As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping solve product and business challenges. The Data team also functions as an in-house, production "customer" that dogfoods Databricks and drives the future direction of the products. The impact you will have: Shape the direction of some of our key data science areas - segmentation, recommendation systems, forecasting, product analytics, churn prediction and insights. Work closely with Engineering, Product Management, Sales and Customer Success to understand product usage patterns and trends and make data-driven decisions, recommendations a

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Director, AI & Data Governance – Data Stewardship & Governance Enablement Overview Mastercard’s Enterprise Data Governance team is seeking a Director, AI & Data Governance to enable data governance across the enterprise through a federated stewardship model. As an established subject matter expert, this self-starter will lead data stewardship within selected business teams and data domains, help refine the Enterprise Data Governance framework, and provide strategic input to enable adherence to data governance policies and standards. The ideal candidate has hands-on experience standing up and scaling data stewardship programs, turning policy and standards into practical, repeatable processes, and influencing stakeholders at all levels to adopt them. This role will report to a Director, AI & Data Governance. Role • Lead and facilitate data stewardship networks, providing guidance, coaching, and escalation support while fostering a culture of collaboration and accountability. • Support stewardship teams by writing and maintaining business glossary terms, critical data elements, classification and transformation logic in the data catalog, translating technical logic into plain language for non-technical stakeholders. • Drive awareness and adoption of data and AI management practices

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Overview CVS Health is seeking a Data Scientist to join its enterprise clinical intelligence platform team. AI is unlocking new possibilities in healthcare at an unprecedented pace, and that progress comes with a responsibility to build capabilities that are clinically rigorous, ethically grounded, and worthy of the trust patients and providers place in them. This role will analyze clinical data and develop AI and machine learning solutions that generate evidence-backed insights for use cases across CVS Health. The Data Scientist will work closely with experienced data scientists, engineers, product managers, and clinical partners to build, evaluate, and improve solutions used in production. What You’ll Do Develop subject matter expertise in clinical data and its application to healthcare problems. Explore, analyze, and summarize large structured and unstructured datasets to inform product and modeling decisions. <span

A Career with Point72's Market Intelligence Team On our proprietary research team—Market Intelligence—you’ll partner with our investment professionals and Compliance team to work with alternative data to uncover insights about companies, industries, and the broader economy through deep fundamental research and applying data science and engineering techniques. You’ll work alongside a talented team with diverse skills, backgrounds, and perspectives. Our sector data analysts, data scientists, data managers, and engineers work together to build compliant research products that are incorporated into the research process of our investment professionals. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. The Data Strategy team within Market Intelligence takes a research-oriented and strategic approach to discovering new avenues of insight, manages the inflow of compliant data into our team’s process, and is responsible for managing effective and efficient data and research partnerships on behalf of the firm. What You’ll Do As a Data Sourcing and Strategy Operations analyst, you will collaborate with our team, colleagues across the firm, and external vendors to provide essential support required to source data and conduct research that may ultimately be used by our investment teams. Specifically, you will: • Assist the Data Sourcing and Strategy team in managing relationships with data and research providers, including facilitating requested service changes, ensuring internal use of services follows the firm’s contracts and obligations, and staying current on the evolving data market • Help manage the team’s operations workflow by working closely with Legal, Compliance, Finance, and other internal stakeholders • Maintain and manage the Data Sourcing and Strategy knowledgebase by developing an understanding of system architecture • Develop strong internal relationsh

About the Team OpenAI’s Research Data team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods through which we acquire and create data. About the Role As a Data Program Manager, Science, you will help researchers develop and execute scientific data programs, connecting OpenAI’s research priorities with relevant data, expertise and external partners. You’ll work closely with researchers to understand their needs, assess the scientific and practical value of opportunities, and develop partnerships across the scientific ecosystem. The work could range from acquiring existing datasets to shaping research collaborations. You’ll carry opportunities from initial investigation through commercial discussions, agreements, delivery and research use, exercising sound judgement around sensitive data and relationships. Our current work focuses particularly on biology and chemistry. We welcome different combinations of scientific, technical and partnership experience. This role is based in our San Francisco HQ. In this role, you will: Develop data strategies with Research. Translate research goals, model limitations and evaluation gaps into evidence needs and success criteria. Compare acquisition with internal, public and commissioned alternatives. Find distinctive sources for research. Build trusted local and international relationships across research and industry, including organisations at the scientific frontier. Assess opportunities in scientific context. Inspect samples for provenance, context, quality and completeness. Assess usefulness, involving researchers and specialists as needed. Shape partnerships with lasting scientific value. Understand partners’ ambitions and define pilots, deliverables and acceptance criteria, considering expertise, scientific contribution and continuing relationships alongside commercial terms. Lead commercial and operational execu

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. We are so excited to now be looking for an experienced public policy and regulatory affairs professional to help us anticipate and navigate a rapidly evolving global regulatory landscape. Reporting to our Senior Director, Public Policy & Regulatory Affairs in London, you'll play a key role in shaping our approach to regulatory change across Europe and globally. You'll lead important elements of our global regulatory readiness programme while supporting the development of policy positions, advocacy strategies and engagement with policymakers, regulators and industry bodies. You'll work closely with senior leaders and teams across the business to assess emerging regulatory developments, understand their potential impact and translate complex requirements into clear, practical recommendations. Your remit will span some of the most important issues affecting the data and technology sector, including AI, data protection, financial crime, consumer protection, ESG, competition and international trade. This is an opportunity to combine regulatory insight, public policy and business strategy in a highly visible global role, helping Dun & Bradstreet respond effectively to regulatory change while supporting responsible innovation and growth. Based in our beautiful offices in Paddington, London, this role works on a hybrid basis with at least 3 days on site and will require occasional travel. What You'll Do: Regulatory Strategy & Readiness Monito

About DataCamp DataCamp's mission is to empower everyone with the data and AI skills essential for 21st-century success. By providing practical, engaging learning experiences, DataCamp equips learners and organizations of all sizes to harness the power of data and AI. As a trusted partner to over 20 million learners and 6,000+ companies , including 80% of the Fortune 1000, DataCamp is leading the charge in addressing the critical data and AI skills shortage. About the role + Responsibilities The Learning Solutions Architect is a customer-facing technical trainer who helps organizations build data and AI capabilities with DataCamp. You’ll deliver engaging live training (virtual and onsite) and create tailored learning materials on the DataCamp platform—think custom courses, projects, certifications and assessments that map to each customer’s roles, tools, and outcomes. You’ll partner with Customer Success, Sales, Product and Content to scope blended learning paths, teach high-impact sessions, and publish reusable, high-quality content that accelerates adoption and measurable skill uplift for some of our most high-value customers. Qualifications Loves to teach. Comfortable spending multiple hours weekly in front of a virtual or onsite classroom. Broad Data Engineering experience with Snowflake/Databricks expertise. 2+ years in technical training, data science/analytics education, solutions engineering, or similar instructor roles. Learns new tools quickly; enjoys tailoring content to different personas (analyst, engineer, business user, exec). Strong communicator who can simplify complex topics for technical and non-technical audiences. Detail-oriented and process-driven; delivers sessions and materials with substance. Flexible schedule to support time zones (this is not a 9 to 5); occasional travel for onsite delivery. Some of your key metrics will be: Customer satisfaction: survey, engagement, repeat bookings Professional services revenue (with a success based

Here at Appian, our values of Intensity and Excellence define who we are. We set high standards and live up to them, ensuring that everything we do is done with care and quality. We approach every challenge with ambition and commitment, holding ourselves and each other accountable to achieve the best results. When you join Appian, you’ll be part of a passionate team dedicated to accomplishing hard things, together. Marketing Data Manager McLean, Virginia, USA | Work Model: On-site at Appian Headquarters Own the health, hygiene, and strategic governance of Appian's global marketing database, establishing measurable standards that enable precision targeting and accelerate pipeline velocity across all regions. ABOUT THE TEAM Marketing Operations creates reliable reporting frameworks based on consistent and segmented data, while creating a frictionless journey from lead to MQL. The team is responsible for the marketing team's data, analytics, lead lifecycle, budgeting, tech & tools. As Appian scales its AI-Powered Process Automation platform globally, this team ensures marketing moves fast with confidence, backed by clean data and automated workflows that drive measurable business outcomes. THE OPPORTUNITY Appian is investing in marketing infrastructure that scales with explosive growth in enterprise AI adoption. This role exists to transform our marketing database from a reactive asset into a proactive growth engine, establishing the data quality standards and governance frameworks that power segmentation, personalization, and attribution at scale. You will define what success looks like, measure it, and drive continuous improvement across global and regional stakeholders. WHAT YOU'LL DO Establish and enforce minimum data quality standards across the marketing database, creating a measurable database health score with quarterly improvement targets reported to global and regional leadership. Architect and execute data hygiene programs within Marketo and Salesforce,

Capco, a Wipro company, is a global technology and management consultancy specializing in driving digital transformation in the financial services industry. With a growing client portfolio comprising over 100 global organizations, Capco operates at the intersection of business and technology by combining innovative thinking with deep industry expertise to deliver end-to-end, data-driven solutions across banking, payments, capital markets, wealth and asset management, insurance, and energy. Capco’s innovation is driven through its collaborative culture, Innovation Labs, and commitment to empowering diverse talent to thrive. Role Summary The Tech Lead plays a key role in leading the design and delivery of scalable, secure, and high-performing technology solutions. This is a hands-on leadership role combining strong software engineering and solution design skills with a solid understanding of data and modern data platforms. Working across the Software Development Lifecycle (SDLC), the Tech Lead works closely with business, product, architecture, and engineering teams to translate requirements into practical technical solutions, guide implementation, and ensure high-quality delivery within Agile environments. What You’ll Do Lead technical design and delivery across applications, integrations, and data-driven solutions Translate business requirements into scalable, maintainable technical solutions Provide hands-on technical leadership, including design and code reviews, troubleshooting, and implementation guidance Define and apply engineering standards, architectural patterns, and development best practices Collaborate with business, product, architecture, engineering, and infrastructure teams throughout the delivery lifecycle Design and build solutions across cloud, on-premise, and hybrid environments Guide application and integration design using APIs, microservices, messaging, and event-driven approaches Apply strong data fundamentals including data mode

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,500 firms in 60 countries use Addepar to manage and advise on nearly $10 trillion in assets. Its open platform integrates with 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and levels of complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, São Paulo, London, Edinburgh, Geneva, Warsaw, Dubai, Pune and Singapore. The Role We are seeking a Lead, Data Validation Specialist to oversee a team of Data Validation Specialists responsible for ensuring the accuracy and integrity of financial data during new client onboarding. You’ll manage daily workflows, ensure consistent data quality across projects, and serve as the primary liaison between the Data Validations team and cross-functional partners. This is primarily a non-client-facing role that plays a key part behind the scenes, requiring focus, consistency, and comfort with repetitive work. It’s a great fit for someone who enjoys working with data in a structured way and takes pride in getting the details right. You’ll be instrumental in fostering a collaborative team culture, driving consistency in our data conversions, and contributing to the growth of both your team and our global function. Applicants must have legal authorization to work in the country where this role is based on the first day of employment. Visa sponsorship is not available for this position What You’ll Do Lead and mentor a team of Data Validation Specialists, supporting career development, delivering regular feedback, and helping individuals thrive in their role Manage a team’s work allocation, prioritization, and exe

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. Fraud Data is the data science and machine learning team within Plaid’s Fraud organization, responsible for using data and ML to improve and scale Plaid’s fraud products. Within Fraud Data, the Customer & Product Intelligence team focuses on understanding product performance, uncovering customer insights, and enabling go-to-market teams with data-driven solutions. The team partners closely with customers and GTM teams on fraud analyses and proofs of concept, turning customer learnings into scalable, reusable product capabilities. We also build the metrics, analytics, and data foundations that measure product health, identify opportunities for improvement, and guide product decisions across Plaid’s Fraud portfolio. As a Data Science Manager, you will lead a team responsible for customer-facing data science and Fraud product analytics. You will set the team's roadmap, develop its data scientists, and remain involved in analytical methods, technical reviews, and customer investigations. You will: Set a 6–12-month roadmap with Product, Engineering, and GTM, and assign priorities and responsibilities across the team. Define product metrics, their underlying data, and reporting and

CAPCO POLAND *We're looking for candidates located in Poland Capco Poland is a global technology and management consultancy specializing in driving digital transformation across the financial services industry. We are passionate about helping our clients succeed in an ever-changing industry. We also are: Experts in banking and payments, capital markets, wealth and asset management Focused on maintaining our nimble, agile, and entrepreneurial culture Committed to growing our business and hiring the best talent to help us get there Role Overview: At Capco, we combine business, data and technology expertise to deliver meaningful transformation across financial services. We are looking for a Data Business Analyst to support a large-scale banking data initiative. This role sits at the intersection of business requirements, data analysis and technical delivery , with a strong focus on translating business needs into well-defined data solutions. You will be responsible for an end-to-end analytical scope: understanding data requirements, identifying and validating source data, defining business logic and mappings, preparing Asset Designs and implementation-ready requirements, and collaborating with Data Engineering teams throughout delivery. This is a great opportunity for someone who enjoys combining hands-on data analysis with business analysis and solution design in a complex banking environment. What You'll be responsible for: Gathering, analysing and refining business and data requirements and translating them into clear technical requirements. Acting as a link between business stakeholders, data teams, architects and Data Engineers throughout the data delivery lifecycle. Identifying relevant data sources across HDP/Hadoop environments and determining how they should be delivered to the analytical layer in Google Cloud Platform . Analysing and validating data using SQL, BigQuery, Hive and Spark SQL . Preparing and maintaining Asset Designs, data mappings and deta

About the Team OpenAI's data and storage infrastructure spans data platforms, online databases, and file/object storage. These systems underpin data ingestion and processing, durable persistence, indexing and retrieval, and product file experiences. As frontier models and agents evolve how they use memory, history and snapshots, the underlying architecture increasingly shapes the capabilities products can deliver—and their latency, reliability, cost and efficiency. About the Role We are looking for a technically deep TPM to independently define and lead multiple programs across data platforms, online databases and storage infrastructure. You will connect model, product and data-consumer requirements to architecture, and work with the relevant engineering teams to take new capabilities through production adoption and repeatable expansion. The design scope is exabyte-scale storage and infrastructure spanning multiple millions of CPU cores. The challenge is not simply forecasting more resources: it is making complete, workload-ready capacity repeatable, with a clear path from product requirements through architecture, deployment and validation. A data pipeline, database query, file operation or execution snapshot can affect whether a product or agent succeeds; you will connect those outcomes to the systems underneath. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Translate model, product and data-platform needs into precise access patterns, consistency, durability, freshness, availability and scalability requirements. Connect memory, history, retrieval and resumable work to capability and end-to-end latency. Partner with engineering to transform data and storage architecture into repeatable scale units: standardized provisioning, placement, routing, data movement and readiness checks that bring storage, compute and networking online together.