Data Scientist, Investment Reporting

Hall Capital Holdings is a family-owned private investment firm, founded in 2006, that invests patient, long-term capital through two complementary strategies: a portfolio of public market securities and direct investments in established U.S. businesses. On the direct side, we acquire majority stakes in, or full ownership of, under-invested companies and work alongside management as operators, not just investors, with no required exit timeline.

We act as a family, not a fund.

We're hiring our first full-time Data Scientist to own data, research, and analytics across both sides of our portfolio. On the private side, you'll build and manage the dashboards our portfolio companies run on and work directly with their leadership to turn operating data into decisions on pricing, margins, marketing, inventory, and growth. On the public market side, you'll support research, monitoring, and reporting for the firm's securities portfolio.

You'll also lead the firm's research work, from product and competitor studies to market and industry analysis, that informs both day-to-day operations and investment decisions. You'll own the work end to end: getting the data, building the dashboard infastructure, and presenting results that decision-makers act on. You'll report to the COO and work closely with the CFO and the deal team.

• Data and analytics dashboards: Design, build, and own a live dashboard for each portfolio company, plus a consolidated portfolio view, covering sales, gross margin, customer acquisition cost, conversion, inventory turns, and cash flow. Set common KPI definitions across companies, automate the data refreshes, and keep the dashboards accurate and current so leadership and operators rely on them to run the business.
• Pricing and competitive intelligence: Own daily competitor price monitoring for our e-commerce companies including product matching, landed-cost comparisons, and price elasticity and promotion analysis that ties pricing to volume and margin.
• Forecasting and modeling: Demand and sales forecasts, inventory planning, customer lifetime value and segmentation, and marketing attribution and return on ad spend.
• Data infrastructure: Connect and clean data from e-commerce platforms (Shopify and Magento), Google Analytics 4, Google and Meta ad platforms, CRM and accounting systems (including Quick Books Online), and spreadsheets. Build reliable, automated pipelines and a central data store that feeds every dashboard.
• Business Improvement: Generate actionable insights for business improvements

• Portfolio reporting: Maintain holdings, performance, and exposure reporting for the public securities portfolio, including position returns, position concentration, and sector exposure, and flag developments that warrant a closer look.

• Research: Lead product research, competitor analysis, and market and industry studies that support portfolio companies and the investment team.
• Deal support: Support the CFO and deal team with data-driven diligence, and market research on new acquisitions, and track value-creation plans after a deal closes.
• AI and automation: Use and oversee AI tools for research, monitoring, and reporting, and set the standards for accuracy, sourcing, and quality control.
• Communication: Turn complex analysis into clear recommendations for owners, executives, and operators who aren't data people.

• Launch a live, automated dashboard for our existing portfolio company and set the KPI framework the other portfolio companies will follow.
• Take ownership of the firm's existing public portfolio reporting, and document how each workflow runs.
• Map the firm's data sources and recommend a plan for a central data store.

• 2-3 years in data science, quantitative research, or advanced analytics, ideally with exposure to investment research (private equity or family office) and operating businesses (e-commerce, distribution, or consulting).
• Strong Python or SQL (pandas, scikit-learn, stats models, or similar), plus hands-on experience building and maintaining dashboards in a BI (Power BI, Tableau, or Looker) or AI tool.
• Hands-on experience with pricing analytics, forecasting, and experiment design or A/B testing.
• Experience building data pipelines with APIs, responsible web data collection, and cloud data warehouses (Big Query, Snowflake, or similar), with sound engineering habits:
  Git, reusable code, and clear…