DataFox SF Team

About Us

Our Story

Before DataFox, we had jobs in which doing manual data grunt work was a prerequisite for accomplishing our real jobs. We decided to use data science and software to solve this problem.

Our mission is to eliminate grunt work for business professionals.

We started with investors and sales teams who needed company intelligence in their CRM. To help them, we built a database of the world’s most relevant companies, using ML and NLP to capture insights on those companies and infuse that intelligence into our customer workflows. This helps them skip the grunt work and jump straight into strategic decision making.

Our San Francisco Team

DataFox is a team of people who value #ConstantLearning. Hover to learn about a memorable learning from each person’s past studies and work experience, as well as favorite thing about the team at DataFox.


School: Discounted Cash Flows and Option Pricing Models at Stanford.

Work: modeling private company growth at Goldman Sachs.

Favorite thing: feel fortunate to work with such a committed, tight-knit team.


School: the expressiveness and complexity of Bayesian modeling

Work: bridging the gaps from static data modeling to a living production system

Favorite thing: learning from the brilliance of each and every one of us


School: How to write clearly, whether in ML code or religious studies essays.

Work: Scaling backend sytems and engineering teams to support tens of millions of users at Box.

Favorite thing: Building a great team and watching them thrive


School: Object-orientation, encapsulation, and inheritance at Stanford

Work: Cross-platform information pipelines

Favorite thing: We live our values


School: For me, calculus is easy compared to statistics, which are really hard

Work: Mapping 300,000 corporate purchases to spend categories

Favorite thing: The blend of professionalism and fun that people bring to the office


School: Startup valuation modeling through an entrepreneurship program

Work: Learning how sales organizations scale at Salesforce

Favorite thing: The team expects a lot from each other but in turn will do anything to help


School: Primary research for competitive intelligence projects

Work: Manually building the training data for Machine Learning models

Favorite thing: Managing more than 250,000 hours of remote team member time


School: Law and economics course on price and incentive theory at Duke

Work: Litigation valuations and fraud investigations at PwC

Favorite thing: Seeing our team grow with professional go-getters


School: Data establishes shared understanding of reality (political economics at Stanford)

Work: Finding best tweets from different perspectives for trending events, Twitter

Favorite thing: dedicated and talented, yet ego-free


School: Number theory

Work: Modeling clients' portfolios based on risk appetite

Favorite thing: Most social group of highly intelligent people around


School: Agent-based modeling in economics

Work: Using financial transactions data to visualize money-laundering networks

Favorite thing: It's easy to ask anyone for help


School: Building an OS from scratch at MIT.

Work: Finding and fixing performance bottlenecks and organizing data at scale

Favorite thing: We take pride in our output and support each other


School: Programming a Pac-Man in Cal's Intro to AI class

Work: Creating Box's first A/B testing framework still used today

Favorite thing: Learning something from one of my coworkers every single day!


School: Dashboard to visualize and interact with contractor data from the Department of Defense

Work: Custom automated rules in AdWords that optimize CPC bidding

Favorite thing: Scrappy, efficient, and ambitious in our projects


School: The difficulty and subsequent satisfaction of learning R in Statistics II at Fordham

Work: Helping to create a global price book while working in the Images department at Associated Press

Favorite thing: Everyone's selfless pursuit of building an amazing customer-centric business


School: Understanding environmental issues (and proposing solutions) through data and science

Work: Evaluating pipeline data to optimize our recruiting funnel - never ending project!

Favorite thing: Our incredibly authentic team


School: Statistics!

Work: Buyer persona definition

Favorite thing: Everyone watches out for each other and has everyone's best interest at heart!


School: The intersection of ethical theory and technological innovation at UCBerkeley

Work: Modeling executive equity ownership and stock options at J.P. Morgan

Favorite thing: As an ex college athlete, the teamwork and collaborative focus


School: Probabilistic record linkage algorithms and rule-based matching

Work: Building internal tools to to match, extract and transform data at scale

Favorite thing: The freedom to get wildly creative in exploring new ways to solve problems


School: Dark matter, pulsars, and magnetars in physics seminar on the cosmos at Stanford

Work: Built a model to optimize commuter shuttle routes

Favorite thing: The people


School: Knot theory and its applications in graduate school

Work: Teaching sabermetrics to high school students

Favorite thing: We challenge and support each other every day


School: Studying data in journalism (and sabermetrics) while pitching college ball

Work: Building a dynamic pricing model at DataFox

Favorite thing: Camraderie between engineering and sales


School: International Politics: Methods of Analysis

Work: Gathering customer feedback to influence product roadmap

Favorite thing: We're small, scrappy and we have each others backs!


School: Communication studies where I learned how to communicate based on my audience

Work: The role types identification project where we took a deep dive on what various roles care about.

Favorite thing: The saturation of intelligence and willingness to help


School: Apply statistical regression models to predict fantasy basketball performance

Work: Calculating potential customer fit with standard deviation analysis

Favorite thing: A team that imposes high standards of work quality to create energy rather than consume it


School: calculating phase delay for course on Sound Engineer

Work: Collaborating with Data Scientist at Triax to establish construction worker 'risk probability' score

Favorite thing: Natural collaboration to make everyone better then they were yesterday


School: Data extraction using SQL in Data Analytics for Business

Work: Created scripts to turn CSV fields into custom search terms

Favorite thing: How our company values get actualized


School: Disaggregating signals with Hidden Markov Models

Work: Training our company news classifier to extract signals

Favorite thing: The team's empathy and willingness to teach each other


School: Empirical Analysis and Quantitative Methods at UC Berkeley

Work: Built a data-driven conference strategy based on target account density at DataFox

Favorite thing: Our ability to aggressively pursue seemingly impossible deadlines as a cohesive unit


School: Aeronautical Engineering

Work: Growth Segment Analysis

Favorite thing: The Team Itself


School: I loved art class as I love visualization and cryptography class because it was challenging

Work: Coding our Insights tab, showing users visuals stats for their searches/data!

Favorite thing: kind, understanding, supportive teammates


School: Building long term valuations for investments, mergers, & acquisitions

Work: Running endless manual data cleanse projects for a financial services firm

Favorite thing: The general hunger to create something new; everyone is a builder


School: Studied painting, minored in art history, focusing on Venetian renaissance and African art

Work: Designed a crop insurance platform for farmers who leverage IoT data

Favorite thing: A great team of smart and nice people


School: Probability distributions in statistics

Work: Mapping ADR contribution to revenue + associated activity using SFDC reporting

Favorite thing: The willingness to always help out and motivate each other


School: Nonlinear speech and signal processing for speech pattern analysis at Marquette

Work: Seamless integration of Salesforce in the DataFox application

Favorite thing: Collaboration and camaraderie amongst a great team of smart engineers


School: Business statistics helped put the power of stats into perspective

Work: Working with engineering to give feedback on account scoring

Favorite thing: The constant competitive energy on the sales floor


School: Language dynamics

Work: Optimizing keywords for search

Favorite thing: Incredible collaboration!


School: Market validation. Entrepreneurship 101:Boots on the ground. Boulder, Co

Work: Rethinking sales processes to cut down on time to close

Favorite thing: Hustle. You're never the first one in at 7am or the last one to leave at 8pm


School: Physics

Work: Statistics and infographic designs

Favorite thing: We ship. Quickly.


School: Marketing research on the return rate and customer satisfaction in the cosmetic field

Work: Using big data analytics to grow Marketing ROI

Favorite thing: we are constantly being challenged & helping each other accomplish our goals.


School: Linear programming in management science at WashU

Work: Building pivot table UI for analyzing aircraft data

Favorite thing: Impressive team members


School: Probability theory and linear regressions in statistics

Work: Led cross-object schema mapping and data migration to Salesforce, Pardot, and Outreach.

Favorite thing: Watching how the team lives up to our reputation


School: Conditional probability and data distributions in Statistics

Work: Equity holding optimization for iShares portfolios

Favorite thing: Every single person is willing and able to help each other out


School: Macroeconomics - It's interesting to understand how the world works

Work: Commodities & FX Desk at Bloomberg

Favorite thing: Leveraging data to scale and prioritize projects

Some of Our Investors


Leo Polovets
General Partner, Susa Ventures

Tom Griffiths
SVP, FactSet Research Systems

Howard Lindzon
General Partner, Social Leverage

Eric Roza
SVP, Oracle Data Cloud

Some of Our Advisors

Erik Nierenberg

Erik Nierenberg

CEO, Litmus

Steve Alesio

Steve Alesio

Former Chairman & CEO, D&B

Ram Shriram

Ram Shriram

Founding Board Member, Google

Martina Cheung

Martina Cheung

Head of Risk Svcs, S&P Global