Job Summary

Job Type


Years of Experience
At least 3 years

Tech Stacks

Job Description

If you are a Data Scientist who wants to build algorithms to power search & recommendations product for a global user base, how does the challenge of working on a database of 300 Million+ records, a user base of millions of users from across 100+ countries, sound like? If this got you excited, read on!

Cactus Labs is looking to hire a Senior Data Scientist who can make R Discovery the best research discovery platform for researchers across the globe. The key ingredient to this is the recommendations engine which needs to ensure every researcher receives his personalized feed of best top 3 papers to read – on the app, web and email inbox right at the start of each day. Think of the Spotify algorithm, the LinkedIn algorithm and the Flipboard algorithm; take inspiration & learn and do what it takes to build an even stronger algorithm to recommend the top 3 papers personalized to each user every day.

  • Build algorithms and design experiments to merge, manage, interrogate and extract data
  • Analyze data and user feedback and iterate on the algorithms. Best algorithms are iterated upon every single day, ours is no different - you will build, test, go-live & capture feedback multiple times every single day
  • Work with product, business and other stakeholders to understand the business goals and formulate an actionable roadmap for experiments and iterations on the algorithm(s)
  • Use machine learning tools, predictive models and statistical techniques to produce solutions to key problems
  • Assess the effectiveness of data sources and data-gathering techniques and improve data collection methods
  • Stay curious and enthusiastic about using algorithms to solve problems and enthuse others to see the benefit of your work

Requirements (Desired skills & experience)
  • A Master’s degree or equivalent experience in Data Science, Compute Science, Mathematics, Machine learning / AI or related fields.
  • 3+ years of professional experience is required, preferably around building and running recommendation engine.
  • Excellent understanding of machine learning techniques and algorithms, such as clustering, k-NN, Naive Bayes, SVM, Decision tree learning, Artificial Neural Networks, etc. and their real-world advantages/drawbacks.
  • Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.
  • Strong computer science fundamentals (data structure, algorithms, architecture and OO design).
  • Experience with one or more general-purpose programming languages: C++ or Python.
  • Passion for solving real world problems and ability to get things done
  • Experience with AWS cloud is a plus.


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