About GrowthFactor
Our platform combines geospatial analytics with AI agents that work alongside customers to streamline their real estate workflows. We pull together data from many sources, (foot traffic, vehicle traffic, demographics, retail business locations, and more), to give our customers comprehensive insights for making informed decisions. Our customers then use our platform to collaborate with third-parties, eliminating the need for a messy and complicated email-based workflow.
We're building a services + software product that allows us to differentiate in the marketplace and build customer trust while maintaining software-like margins. We've built an MVP that's already generating ~$600k ARR and secured funding to scale our impact.
We're a lean team with the MVP already in-market. Now we're looking to accelerate our growth and expand the capabilities of our product.
The Role
We're seeking a founding data scientist to build the analytical engine that powers location intelligence for enterprise retail brands. You'll report to our CTO and work directly with leadership to develop models, algorithms, and analyses that influence millions of dollars in real estate decisions.
This role sits at the intersection of data science, ML engineering, and consulting. You'll build production models, develop spatial algorithms, and work directly with customers to solve their site selection problems.
What You'll Actually Do
Week-to-week, you'll be:
- Building predictive models in Python (scikit-learn, PyTorch, XGBoost) on our 60TB geospatial dataset
- Developing spatial algorithms for trade area forecasting, cannibalization analysis, and portfolio optimization
- Writing SQL queries against BigQuery to extract features from foot traffic, demographics, and competitor data
- Conducting ad-hoc analyses for customer requests—"Should we expand in Phoenix or Austin?" or "Which locations are underperforming?"
- Designing geospatial visualizations (heat maps, isochrones, density overlays) to communicate spatial insights to non-technical stakeholders
- Presenting findings directly to customers (VPs of Real Estate, CFOs) in strategy calls
- Collaborating with engineers to turn your notebooks into production API endpoints
In your first 90 days, you'll:
- Ship your first customer analysis in week 3
- Build and deploy a customer-specific model (examples: predicting new location revenue, identifying expansion opportunities)
- Contribute to our core forecasting capabilities
- Present your work to customers and see your analysis influence their decisions
As we scale, you'll:
- Develop novel algorithms for spatial analysis problems without off-the-shelf solutions
- Build customer-specific models that combine their sales data with our geospatial features
- Mentor future data scientists and establish modeling best practices
- Shape our data science roadmap by identifying high-impact problems
- Work with engineers to deploy your models at scale
Technical Skills We're Looking For
Must-haves:
- 3+ years building and deploying ML models in production
- Strong Python skills (pandas, numpy, scikit-learn, PyTorch or TensorFlow)
- Experience with spatial statistics and geospatial analysis
- Solid SQL skills for feature engineering (we use BigQuery)
- Can present technical findings to non-technical stakeholders
- Track record of shipping models that created business impact
Bonus points for:
- Geospatial ML experience (H3, GeoPandas, Shapely, PostGIS)
- Built forecasting models for time series or spatial-temporal data
- Worked with location-based businesses (retail, real estate, logistics)
- Experience with optimization algorithms
- MLOps practices (model versioning, monitoring, A/B testing)
- Early-stage startup experience
Example Projects You Might Own
- Trade Zone Forecasting: Predict customer draw patterns for new locations by analyzing foot traffic flows, road networks, and competitor positions
- Portfolio Optimization: Identify the optimal set of new locations from thousands of candidates while minimizing cannibalization
- Relocation Analysis: Analyze existing store performance, identify better nearby locations, and quantify expected lift from relocating
- Custom Revenue Models: Build forecasting models for specific customers that combine our data with their sales history and operational metrics
- Competitive Impact Analysis: Forecast how new competitors affect existing store revenue based on historical patterns
The Work Split
- Research & Development (40%): Develop new algorithms, experiment with modeling approaches, solve novel spatial problems
- Production (30%): Work with engineers to deploy models, build pipelines, ensure scalability
- Customer-Facing (30%): Conduct bespoke analyses, build custom models, present findings
You'll work with 60TB of geospatial data including foot traffic, demographics, and competitor locations. We're early enough that you'll shape our modeling approach, but mature enough that you'll have infrastructure and real customers from day one.
Our Values & Culture
We're looking for someone who naturally aligns with how we work:
Builder's Mindset: You have hands-on experience creating things from scratch and understand the complexities of building software.
Product-First Thinking: You naturally think about how engineering decisions impact real users and business outcomes.
Problem-Oriented: You instinctively dig into the underlying problems and user needs before jumping to solutions. You ask "what's really going on here?" and ensure we're solving the right challenges.
Direct Collaboration: You prefer working directly with teammates over formal processes
Process-Light: You're allergic to meetings and ceremonies that don't add clear value. You prefer lightweight coordination and focus on shipping great software.
Intellectual Honesty: You speak up when you have good ideas, regardless of hierarchy. You engage in candid technical debates and help create an environment where the best ideas win.
What we Offer
- Competitive cash compensation plus founding team equity
- Direct impact on product and technical direction
- Comprehensive benefits package
- Professional development budget and conference attendance
- Flexible work environment - hybrid model with 3 days in our Cambridge, MA office and strong remote work policy for extended periods
- Freedom to choose the right tools
Salary Range:
120-170K + Bonus & Equity
Next Steps
Ready to help build something from the ground up? We'd love to hear about your experience with geospatial systems, your approach to technical leadership, and how you think about balancing engineering excellence with product velocity. Email Sameena & Raj with the following:
- Your resume
- Examples of geospatial or mapping projects you've worked on
- Your experience leading technical initiatives or teams
- How you approach making product decisions as an engineer
- Why you're excited about joining a founding team
We're an equal opportunity employer committed to diversity and inclusion. We welcome applications from candidates of all backgrounds and experiences.