Job Openings Senior Data-Scientist

About the job Senior Data-Scientist

As a Data-Scientist, Heepsy is possibly one of the best places to enjoy all the different challenges that we face every day. You will enjoy working with categorization problems, regarding social network information, and you will train and enhance different models. Also you will have the opportunity to work with cutting edge technologies on a daily basis. Identify trends and patterns, invent new ways of looking at data, and get creative in order to drive improvements on both existing and future products.

You will be part of the data team, the ones who provide the base for all our products. You will constantly be in touch with real product needs and be an active part of how the data transform and reach our final products.


    University degree/ Education, preferably in Statistics, Computer Science, Mathematics, Physics or similar quantitative oriented discipline. 

    * 3 years of experience working in a data-focused role.

    * Strong foundation in statistics and mathematical models.

    * Experience building data visualizations

    * Strong proficiency in Python, SQL

    * Python model development.


    * Strong verbal and written communication skills.

    * Experience with data science tools such as Pandas, scikit-learn, Numpy.

    * Confident with Machine Learning tools.

    * Experience with distributed computing systems like Haddop and programming languages (PySpark, SparkSQL, TensorFlow).

    * Experience with statistical analysis techniques including linear regression/least squares, experimental design, hypothesis design, confidence intervals, t-test etc

    * Experience in software development and are confident with developing the full ML model lifecycle from research to production ensuring aspects such as reproducibility and scalability.

    * Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

    *  Ability to develop experimental and analytical plans for data modeling processes, use of strong baselines, and an ability to accurately determine cause and effect relations