The role of the Data Scientist is to act as an analytics translator, communicating complex data related requirements between business and IT stakeholders.
He/she will be involved in building of new, bespoke advanced analytic tools.
Key Accountabilities of the role:
Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
Mine and analyse data from company databases to drive optimization and improvement of product development, marketing techniques and business strategies.
Assess the effectiveness and accuracy of new data sources and data gathering techniques.
Develop custom data models and algorithms to apply to data sets.
Use predictive modelling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes.
Develop company A/B testing framework and test model quality.
Coordinate with different functional teams to implement models and monitor outcomes.
Develop processes and tools to monitor and analyse model performance and data accuracy.
Specialist Skills / Technical Knowledge Required for this role:
Knowledge of statistical and data mining techniques (regression, decision trees, clustering, neural networks, etc.)
Knowledge of additional programming languages is a plus (Python, C++, Java)
Intellectual curiosity, along with excellent problem-solving and quantitative skills, including the ability to disaggregate issues, identify root causes and recommend solutions
Distinctive communications skills and ability to communicate analytical and technical content in an easy-to-understand way
Experience required:
Bachelor’s degree in quantitative field like Computer Science, Engineering, Statistics, Mathematics or related field required. Advanced degree is a strong plus
0-2 years of hands-on mathematical modelling experience in business environment
Proven experience in working with datasets and relational databases (SQL).
Strong knowledge of one or more data science or decision science domains (e.g. [un)] supervised learning, explainable artificial intelligence, econometrics, deep learning, Natural Language Processing, time series forecasting, deployment, causal inference, uplift modelling, and/or optimization)
Ability to describe analytic processes from start to finish in your area of expertise
