Data Science Team Lead
Forter is looking for an excellent Data Science Team Lead to join our team!
Forter delivers real-time, completely automated, fraud and abuse protection for online merchants. Our revolutionary technology allows vendors to focus on business opportunities while always staying ahead of the fraudsters. Forter's SaaS solution combines advanced cyber intelligence, identity analysis, and behavioural data in order to create a multi-layered fraud detection mechanism.
Forter is backed by well-known VCs (Sequoia, NEA, Scale Venture) and is growing tremendously fast! We’re looking for a passionate person with a vision and a great attitude to grow with us.
Stuff you’ll be doing:
Be at the unique leader, at the junction of fraud-analysis, data science, and system flow Engineering to extract insights and deliver a component of logics, central to what we do:
- Bring the Data Science to punch in finding the best Models and features to capture the way fraudsters behave to improve real-time detection, in light of intelligent adversaries.
- Find techniques for automated learning from our data, which is meso-big and only sometimes tagged. In particular, lead the Machine Learning revolution in new fields where inference was so far heuristic.
- Communicate research results, solutions and complex ideas to peers, management, and customers. Be the Data Science face of the company.
- Measure and enable Info-gain-based introduction of new features into our system.
- Define and develop the way we should synthesize large corpus of analytical knowledge insights into a scalable streamed flow
- Develop measures, metrics and uses for our large graph of humans & ‘what they use on the internet’ entities.
- Working with colleagues from various disciplines - Research Engineers, Analysts, and your Data Scientists (all of whom write production code!)
Experience you’ll need:
- Proven record of at least 3 years of leading a team of experienced data scientists with clear KPIs and results that moved the needle.
- Proven ability to work well sideways (with peers and vendors) and upward (with management). Proven ability to communicate with customers; you are part of the sales cycle to the big enterprise customers.
- Proven ability to manage well. Your people are very effective, happy and energised, and grow.
- A PhD or M.Sc. in a quantitative field (e.g., Statistics, Economics, Sciences, Engineering, CS)
- Delivery oriented and capable: Algorithms, processes, specifications to R&D.
- Proactive. Tell us where we can use data more effectively, but we currently do not. Draw the boundaries of what possible - you are the expert.
- Knowledge of statistical methods, Bayesian probability, and machine learning techniques
- Background in: Python, SQL, Spark
- Experience with Big Data, including parallel processing of NoSQL data stores - a plus.
- Can work independently given abstract tasks, understand and influence research for data.
- Professional proficiency in English
We appreciate if you had:
- Been involved in a machine learning project (personal hobby, Kaggle contest, etc.)
- Worked with not-so-big-data, skewed and noisy labeling, non-stationary world... but could still extract the best information possible.
- Open source projects you’ve created or contributed to.
- Interesting problems you’ve dealt with, that weren’t trivial.
- Side projects that you couldn’t resist building.
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