Working in a multidisciplinary team, you'll often start by looking at a business problem statement and then start experimenting with different modeling approaches to developing industrialized applications powered by Machine Learning.
Role Responsibilities: Common tasks you’ll focus on will include:
Contributing towards potential solutions to a range of business problems using Data Science.
Developing experimental models and machine learning applications in Python alongside our ML Data Engineers (who build the data pipelines to ensure quality).
Deliver production Machine Learning models which can support a broad range of initiatives.
Complex statistical analysis.
Experience working as a mid to senior-level data scientist in a commercial environment.
Ability to work with business stakeholders, understand their issues and help devise solutions using the relevant data and platforms.
A strong commercially applied knowledge of Statistical Modelling and/or Machine Learning techniques is required such as: regression, clustering, attribution (econometrics / MMM), decision trees and gradient boosting machines (random forest, XGBoost, LGBM) and significance testing.
An intermediate to high level of skill programming using Python is required including how to write modular Pythonic code, familiarity with the core Python data structures and fluency with pandas, scikit-learn, matplotlib.
Intermediate-Advanced level of skill using SQL.
The ability to present the takeaways from these techniques in a clear, visual manner to support senior business partner's decision making is key to the success of our projects