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You will be updated with latest job alerts via emailOur data team has expertise across engineering analysis architecture modeling machine learning artificial intelligence and data science. This discipline is responsible for transforming raw data into actionable insights building robust data infrastructures and enabling datadriven decisionmaking and innovation through advanced analytics and predictive modeling.
As a data scientist at should be able engage with these questions:
1 Explain the assumptions underlying a linear regression and why they matter.
2 How would you think about modelling the purchase decision for a personal computer (eg to build a recommendation engine)
3 Explain the difference between precision and recall and how one balances between them.
4 Explain Bayes Theorem. Compare Bayesian predictions with those from a Neural Net model.
Qualifications :
Key skills:
1. Methodology: Understanding pattern learning algorithms for regression and classification.
2. Modelling: Finding ways to represent the real world in simple ways that can be solved using numbers.
3. Measurement: Defining and tracking the right metrics to evaluate performance.
4. Probability (Advanced): Using probability theory to improve models and decisionmaking.
Typical Output: Models that predict behaviour with a high precision.
Typical Technologies: Jupyter Notebook Scikit Learn TensorFlow/Torch
Typical degree: Maths Science
Additional Information :
Discover some of the global benefits that empower our people to become the best version of themselves:
At Endava were committed to creating an open inclusive and respectful environment where everyone feels safe valued and empowered to be their best. We welcome applications from people of all backgrounds experiences and perspectivesbecause we know that inclusive teams help us deliver smarter more innovative solutions for our customers. Hiring decisions are based on merit skills qualifications and potential. If you need adjustments or support during the recruitment process please let us know.
Remote Work :
No
Employment Type :
Fulltime
Full-time