Data Scientist

Tel Aviv
Full Time
Engineering

We’re a well-funded start-up that focuses on changing the way people leverage data to make decisions. We believe that out-of-context dashboards are not the solution but the problem, and we’re obsessively passionate about helping people take data-driven actions! 

This is not a classic data role:

  • You will be joining the founding team.
  • You will help the biggest product companies in the world leverage their behavioral data using state-of-the-art data science methods to support their next products’ decisions.
  • You will work with the R&D team on developing a platform that automatically turns data into concrete opportunities.  

You will:

  • Develop large scale innovative data science models
  • Work together with the R&D team to design automatic processes that automate the model development process
  • Partner with product managers and growth experts to identify the most important business questions and opportunities
  • Help building a methodology for designing and evaluating experiments

You should have:

  • 2+ years of experience as a data scientist
  • Experience with modern data tools and frameworks (ex: Pandas, Numpy, XGBoost, Scikit-Learn, etc)
  • Deep understanding of modern machine learning algorithms and statistics
  • Being able to own your models from development to production deployment
  • Excellent communication skills to explain results to product managers, data analysts and engineers
  • Experience with Big-Data tools like Spark or BigQuery – Advantage
  • Experience with Causal Inference – Advantage
  • Passion and motivation to build a growth machine.

*This is not a fully remote position. 

What will you do? 

  1. Define and build robust analyses that will be included in our core product.
  2. Run analyses on customers’ data and translate them to product requirements. 
  3. Engage with customers to help shape the data strategy of the product. 
  4. Work very closely with the product managers to build the product roadmap and with a team of world-class data scientists. 
  5. Share users’ insights across the company to create a learning organization. 
  6. Define KPIs and analyze metrics to track the success of the product.
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