Do you have Machine Learning experience as well as a love for data infrastructure skills? Do you have a solid grasp of statistics and higher-order math? Are you “neurologically diverse”? Have you ever focused on creating high-value technology in the middle of the chaos of a small, rapidly-growing company? Can you say that you hit specs on time, every time, and “on quality”?
This position involves both architecture and programming. It primarily involves the rapid integration and analysis of **both** traditional/structured data and non-traditional/unstructured data sources to accomplish model building and machine learning…all toward generating predictive analytics about people.
What You’ll Do
- Design and lead a team to build our Big Data and Machine Learning infrastructure.
- Model development by thinking creatively about features – seeking to devise scores for trustworthiness across functions like Identity (KYC), Fraud prevention and Character/Capacity in Lending.
- Conduct feature engineering work.
- Employ machine learning, Neural Networks, Random Forest & other best-in-class modelling techniques to impact decision’ing across multiple departments
- Integrate non-traditional data with traditional financial data to build on one of Trust Science’s core competencies in the area of social graphs and their contribution to our Six°Score™
- Effectively communicate complex and technical analyses to senior management with the opportunity to help drive business strategy & our technology roadmap in this high-impact role
- Be a thought leader in the area of data/analytics/technology & champion the latest cutting-edge techniques to keep Trust Science at the forefront of the fast-paced FinTech world
What You’ll Need
- A PhD or Master's Degree (or completing one of these very soon) in Computer Science or a related field
- Advanced knowledge of Data Architecture and Data Pipeline
- Breath-taking coding and analytical skills...more like being "gifted" in this regard
- World-class experience prototyping & developing real-world ML & RL models
- Hands-on experience with Deep Learning or Probabilistic modeling is required
- NLP knowledge and expertise
- Cloud computing experience (AWS/Azure and DataBricks are all required)
- An extremely strong work ethic & dedication. We are not a lifestyle company which is why a piece of the company is part of the prize. Our CEO leads by example, around the clock
- Strong, fluent command of English and any one other human language
If you have the risk tolerance to join a young company on the ground floor, then let's do this!
Don't bother giving us character references from friends or peers. It will be much more impressive if you get your prior supervisors (and, also, their boss...i.e. your boss's boss) to pitch you to us. We’d especially like it if you have worked for owner-managers in the past. Tell why we need you on our team.
If you have any work product that you're proud of--e.g. a difficult problem that you solved--throw in a link to a project or code snippet. Or give us your Stack Overflow or Git alias.
Our CEO looks forward to hearing from you!...he's eager to build another major, world-class team, which he and his brother have done before. Check our “About” page where you’ll also see the immediately-prior CFO of Facebook: https://www.trustscience.com/about/ who is an investor and advisor to the CEO.
Trust Science has over 20 patents in 6 countries, with many more pending. We are innovating a brand new way to think about people, starting with intelligent search and moving all the way through to building social graphs and geo-activity heat maps.
We are short on time, so everything needs to happen “yesterday” given how fast this space is moving and given how demanding (and big) our opportunities are! Our main competitor was global—at least they were, until they very recently got bought out by a household name, multi-billion$ player. Now it’s our turn to shine...fast! Our mission is an important one = help people who can’t get credit or who are under-banked like Millennials and immigrants. We help businesses to see the best in everyone by digitizing their trustworthiness.