Data Research Analyst Financial Services (Remote)

📋 Description

• • Own the end-to-end research pipeline that powers Forbes Advisor’s authoritative coverage of financial services products. You will translate editorial questions into data-driven investigations, ensuring every chart, ranking and recommendation is backed by rock-solid evidence.
• • Scope incoming data requests from editorial, SEO and methodology teams, quickly assessing feasibility, sample size, collection cost and long-term scalability. You will triage competing priorities and publish a transparent research roadmap that keeps every stakeholder aligned.
• • Lead a distributed team of junior researchers across multiple time zones. Assign daily tasks, set quality benchmarks and coach analysts on best-practice techniques for scraping, surveying and manual data capture. Within six months you will formally line-manage one analyst, running monthly 1:1s and quarterly development reviews.
• • Design and maintain a rigorous quality-control framework. Run automated and manual checks on every dataset, flag anomalies, document fixes and feed lessons back into process playbooks. Your standards will become the benchmark against which all Finserv research is judged.
• • Build interactive Tableau dashboards that transform raw product features, pricing and customer-experience metrics into clear, story-ready visuals. Deliver these assets against tight editorial deadlines while preserving pixel-perfect accuracy.
• • Perform deep-dive analyses on US lending markets—personal loans, small-business credit, mortgages, BNPL and emerging fintech products. Surface market leaders, hidden fees and consumer sentiment trends that directly influence star ratings and “Best Of” lists read by millions.
• • Partner with the SEO team to identify high-value keyword gaps, then craft research plans that generate the proprietary data needed to win those SERPs. Your work will translate directly into traffic growth and affiliate revenue.
• • Maintain a living taxonomy of financial products, updating schemas as new features (e.g., crypto rewards, ESG scoring) enter the market. This metadata backbone will power comparison tables, filters and dynamic calculators across Forbes Advisor sites.
• • Present findings in concise Slack updates, weekly stand-ups and monthly “data deep dives” attended by editorial leadership. Translate complex statistical outputs into plain-English takeaways that non-technical stakeholders can act upon.
• • Continuously improve data-collection efficiency by scripting repeatable workflows in SQL and Python. Your automations will cut manual hours by at least 30 % within the first year, freeing the team to tackle higher-order questions.
• • Champion a culture of documentation and knowledge sharing. Publish internal wikis, run lunch-and-learn sessions and mentor colleagues on SQL joins, regex extraction and Tableau parameter tricks.
• • Stay ahead of regulatory changes and market entrants so that Forbes Advisor ratings remain current and defensible. When the CFPB releases new guidance or a fintech unicorn launches, you will be the first to assess the impact on our datasets and scoring models.