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ML Engineer / Data Scientist



Here is the breakdown of the most important parts of your role:

  • You will develop and apply a range of statistical, predictive models on data sets to extract trends and outcomes that can predict future performance of client products;
  • You will select features, build and optimize various classifier models using machine learning techniques;
  • You will perform processing, cleansing and verifying the integrity of data used for analysis;
  • You will do ad-hoc analysis and present results in a clear manner;
  • You will extend the data with third party sources;
  • You will enhance data collection procedures to include relevant information for the analysis.


Qualifications and Experience

We are looking to expand our team with open, thoughtful, and adaptable colleagues who have 3+ years experience with the following:

  • Machine learning techniques such as Decision Trees, Naïve Bayes, SVM, Neural Networks, Deep neural networks;
  • Proficient in using Python, but also R or C/C++;
  • At least one of the data science toolkits, such as R, NumPy, Scikit-learn, Weka, MATLAB;
  • Query languages , such as SQL;
  • At least one NoSQl database, such as Mongo DB, Cassandra;
  • Statistics skills, such as distributions, statistical testing, regression;
  • Data visualization tools; 
  • SDLC in general (Planned Iterative, Agile);
  • Good spoken and written English language skills.


Endava’s philosophy is to both challenge and support you to do the best work of your career.


Additional Information

Additional benefits:

  • Private health insurance, monthly sports allowance & meal tickets;
  • Loyalty annual leave days & replacement days for weekend bank holidays;
  • Various options for purchasing Endava shares at a preferential price;
  • Referral bonus;
  • Work from home and flexible working hours;
  • Multiple offers and employee discounts;
  • Ongoing learning opportunities – complex projects, trainings, coaching, conferences, workshops, certifications, online learning platforms subscriptions etc. ;
  • Diverse company social life - events, sports tournaments, team buildings, passion groups (e.g. hiking, book club, green team);
  • Multicultural environment - working with colleagues and clients across different countries.

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