Business teams are held back by the amount of data they need to find and manage. Every CRM today requires that organizations painfully build and maintain a database of businesses they might one day sell to; it’s an impossible task.
At DataFox we believe that every business should have a scalable solution for getting actionable, real-time insights on the companies they sell to without the grunt work so that employees can focus on what matters most - building relationships and growing their business.
...(and we're hiring!)
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
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: Designing marketing strategy to create, deliver, and sustain customer value
Work: Aligning the content strategy with marketing automation tools
Favorite thing: The collaborative team dynamic that supports and upholds our values
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
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
...(and we're hiring!)
Former Chairman & CEO, D&B
Founding Board Member, Google
Head of Risk Svcs, S&P Global