• Manipulate databases • Communicate with clients to understand areas where we can contribute to their business • Combine internal solutions or create new ones, applying a variety of techniques and with the freedom to propose new approaches • Develop ad hoc studies and statistical analyses • Interpret the results obtained and assess how they apply to clients' problems • Interact with various Serasa departments and external clients

• Data Retrieval: Pull enriched competitive advertising datasets (spend, placement, and creative data) from MediaRadar's internal tools for assigned accounts and projects. • Share-of-Spend Analysis: Analyze share-of-spend activity across a brand and its competitors to identify which advertisers are gaining or losing ground. • Creative Surfacing: Run scripts and use internal tools to surface top-contributing creative assets tied to spend activity, rather than locating them manually. • Early Hypothesis Development: Extract metadata and themes from creative and spend data to build an early, data-backed hypothesis (e.g., “advertisers are leaning into rewards messaging this quarter”) that senior analysts can validate and build into a client-ready story. • Quality Assurance: Check data for anomalies or inconsistencies before handing off analysis to the client-facing analyst team. • Multi-Account Support: Provide analytical support across several accounts and projects rather than a single dedicated client, gaining broad exposure to different verticals and use cases. • Frontline Analyst Team Support: Serve as the supporting analyst behind our client-facing team, handling the groundwork so senior analysts can focus on client strategy and delivery. • AI-Forward Tooling: Use AI tools, including Claude, as part of your daily workflow to speed up data pulls, first-pass analysis, and reporting — while learning when to rely on it and when to apply your own judgment. • Skill Building: Learn MediaRadar's data taxonomy, internal tools, and analytical methodology with the goal of progressing toward a client-facing analyst role. • Team Collaboration: Work closely with the analyst and project management team to understand project goals and deliver work on time.

• Partner with trading partners to understand business and data integration requirements during implementation and onboarding. • Analyze incoming customer data and perform gap analysis to identify discrepancies, missing information, and opportunities for improvement. • Configure and implement customer integrations using existing proprietary data mapping and transformation requirements. • Communicate integration specifications to customers and business partners, recommending enhancements to file layouts, naming conventions, and data structures when needed. • Collaborate closely with Software Development and Product teams to support enhancements to existing integrations and implement new capabilities. • Validate imported data to ensure accuracy, completeness, and successful processing. • Monitor daily automated data integrations across more than 460 business partners, proactively identifying and resolving data issues. • Investigate and troubleshoot data integration failures, working directly with internal teams and external partners to drive timely resolution. • Support internal and external customer inquiries related to data transformation, file processing, and integration workflows. • Prioritize multiple implementation projects and support requests while meeting established business deadlines. • Contribute to continuous improvement initiatives that enhance integration processes, data quality, and customer experience.

Role Description You'll join one of our sector teams — covering industries like consumer goods, software, or financial services — where you'll own data products that help the world's top investors understand company performance, market trends, and competitive dynamics. Our sector teams are where the core analytical work happens: building and maintaining the data products that our clients depend on for high-stakes decisions. As a Data Analyst, you'll ramp quickly onto a portfolio of data products, building deep expertise in our proprietary datasets and methodologies. You'll take full ownership of your products — ensuring accuracy, improving methodologies, and delivering insights that clients trust. Over time, you'll expand your scope: taking on more complex products, identifying opportunities to improve how your team works, and growing into a key contributor who shapes how we deliver value. This is a role for someone who wants to go deep on hard analytical problems, takes pride in getting the details right, and is motivated by owning work that matters. You'll work closely with your Data Lead, Research Analysts, and cross-functional partners in Engineering and Product to deliver best-in-class outputs — and you'll be expected to bring ideas, not just execute on others’. - Own data products end-to-end — driving product success by delivering best-in-class outputs with a focus on accuracy, client value, and efficiency. - Work with massive amounts of data to answer our clients' key questions about the companies and datasets we analyze. - Tackle complex data problems using strong analytical judgment to refine methodologies, test new datasets, and solve challenges that require creative thinking. - Use AI and tooling to drive meaningful leverage — increasing speed, reducing manual work, and automating portions of workflows. - Collaborate cross-functionally with Research, Engineering, and other teams — coordinating across functions to unblock work, align on best practices, and develop solutions. - Identify opportunities to improve products and processes — whether that's refining a methodology, exploring a new dataset, or finding a better way to do something. Qualifications - 3-5+ years of experience in data analytics, with a background in fields like financial services, management consulting, data science, or high-growth technology. - Strong fluency in SQL, with experience using Python or PySpark as a plus. - Track record of quickly learning new concepts, particularly complex data methodologies, and building strong mental models. - Tackled complex analytical problems and taken ownership beyond immediate scope. - Ability to communicate complex concepts clearly — including methodology, risks, and tradeoffs. - Active use of AI tools and excitement about using AI to drive leverage. Benefits - Flexible work hours and vacation. - Generous 401K match. - Parental leave. - Team events. - Wellness budget. - Learning reimbursement. - Annual base compensation anticipated to be $130K-$180K. - Total compensation package includes a mix of base, bonus, equity, and benefits. - This role may be performed fully remotely within the United States. Company Description YipitData is the leading market research and analytics firm for the disruptive economy. Our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like Consumer Goods, AI & Software, Cloud, Payments, and more. We operate globally with offices in the US, APAC, and India. Our award-winning, people-centric culture emphasizes transparency, ownership, and continuous mastery.