Data scientist

We’re looking for an experienced data scientist with a strong background in modeling and model evaluation to help us develop and optimize our core algorithms for AI Assurance. Superwise’s solution offers practical capabilities to monitor ML models and gain insights into their behavior in a live production environment. Our mission is to help data science teams to scale their AI effectively. 

As a data scientist you’ll develop and optimize algorithmic solutions for complex, real-world problems in a wide variety of use cases like models performance management, optimization, anomaly detection, bias detection, explainability and more, across multiple industries (fintech, marketing, gaming, etc.). You will also take a critical part in our thought leadership efforts by initiating and collaborating on pieces of content and other articles to help educate the data science and MLOps community.


  • M.Sc in a relevant (STEM or related) field with 3-5 years of hands-on experience, ideally in early stage startups or deep tech companies. 
  • Deep knowledge of algorithms, statistics and ML concepts
  • Experience in solving a wide variety of ML tasks (classification, regression, ranking, clustering, anomaly detection, etc.) 
  • Combination of strong research & engineering skills. Proficient with Python and MLDL related packages (pandas, scikit, keras, tensorflow, etc.). Experienced in SQL
  • Analytical, creative thinker with problem-solving skills
  • Ability to perform fast algorithmic poc’s to test future features feasibility.  
  • Good communication skills, ability to clearly explain complex concepts both in writing and orally
  • Writing skills to communicate, explain and share methodologies and thought leadership content

Nice to have:

  • Vast experience in time series anomaly detection – an advantage.
  • Experience with ML explainability methods and strategies.
  • Experience with docker and kubernetes environments.
  • Experience with maintaining  ML models in production and improving performance after deployment
  • Content writing

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