TradeSmith - Data Analyst - Hybrid​/Remote

About Trade Smith

Trade Smith builds investment research tools and data infrastructure for individual investors and financial publishers. Our platforms power Trade Smith's own product suite and the data tools behind Investor Place, one of the largest independent financial publishers in the US. The vendors, datasets, and calculations underneath all of it -- that's what this role owns.

We need someone who actually wants to live in the data. Not manage it from a distance, not hand it off -- own it.

This is a hands-on individual contributor role on our data, algorithm, and calculations team. You are the person who can answer "where does this number come from, what are we allowed to do with it, and is it right?" -- and then go prove it.

The center of gravity is our data catalog: the vendors we buy from, the datasets they provide, the thousands of fields we store, and the calculations we build on top of them, spanning both Trade Smith's product suite and Investor Place's tools.

Strategy and delivery oversight sit with the Director of Technology Operations. Your job is execution inside the data -- tracing lineage, writing SQL, validating calculations, troubleshooting issues, and documenting what you find. You will work alongside our existing team and partner daily with our offshore development and data team.

This is also a growth seat. The right person is someone we can develop into broader data leadership as the team and platform mature. That requires genuine curiosity about the business, not just the data.

• Own and maintain our data catalog -- vendors, datasets, fields, and calculations -- keeping every entry current as the underlying data and agreements change
• Trace individual fields and calculated values back to their original source; the lineage of any number should be documented and defensible
• Keep confidence and status markers honest (confirmed vs. draft) and work the open-items queue down rather than letting unknowns accumulate
• Document data usage and licensing constraints per vendor -- what we can and cannot show customers

• Write your own SQL to pull, join, trace, and validate data -- no waiting on someone else to run queries for you
• Validate calculation engines and derived metrics against their inputs; reconcile figures across datasets and products
• Investigate discrepancies end to end and flag root causes clearly
• Prepare clean, well-labeled data inputs and extracts for the engineering and offshore teams

• Partner with the PMO on intake: help triage and validate data-related requests entering the queue
• Support the broader data, algorithm, and calculations team with hands-on troubleshooting
• Help Customer Service investigate reported data issues -- "why hasn't the closing price updated?" -- and provide clear answers or route them to the right owner

• Track what each vendor agreement licenses us to receive and use; surface renewals, gaps, and usage-rights questions to the Director of Technology Operations
• Keep the data holdings record accurate enough that leadership can rely on it for decisions and audits

• Use AI tools (Claude and similar) to accelerate data mapping, documentation, and repetitive data tasks
• Help shape how those tools fit into our workflows and contribute hands-on to the next iteration of our data platform

• Keep documentation current and readable -- "ask the Data Analyst" and "check the catalog" should give the same answer
• Write findings and summaries plainly for both technical and non-technical readers

• 2+ years in a hands-on data role -- data analyst, data coordinator, data steward, reporting analyst, or similar
• Working SQL proficiency: you write your own queries to trace, join, and validate data
• Strong spreadsheet skills (Excel or Google Sheets), including comfort with large and messy datasets
• Exceptional attention to detail and follow-through; you get real satisfaction from accuracy and getting the small things right
• Clear written communication; your documentation can stand on its own
• Self-directed -- you thrive on execution in an environment where processes exist but are still being built
• Interest in growing into broader data responsibility over time

• Fintech, financial services, or media/publishing data background
• Familiarity with data catalogs, data lineage, or data governance concepts
• Experience using AI tools (Claude, Copilot,…