DescriptionKey Responsibilities:
- Work with senior data scientists to explore, pre-process and analyse datasets to derive new insights.
- Contribute to relevant business presentations for senior management to walkthrough the analytics solution & insights.
- Work with fellow data scientists, data engineers and central tech team to deploy the solution in production.
- Liaise and support business stakeholders throughout the project lifecycle.
- Follow software best practices to code and document the solution
Requirements:
- In depth knowledge of supervised and unsupervised ML Models – linear & logistic regression, clustering, tree-based models like random forest, bagging and boosting models.
- In depth knowledge on feature engineering techniques, hyperparameter tuning and model evaluation.
- Proven track record of applying ML models to solve & measure business impact.
- Proficient in coding - Python & SQL programming
- Intermediate level knowledge of data science frameworks like Pandas, NumPy & visualization libraries like Seaborn, Plotly etc.
- Proven track record of learning and application of relevant business context required to solve the problem at hand.
- Good communication and presentation skills to explain the findings and insights from analysis to business stakeholders.
- Knowledge of software best practices, CI/CD, Cloud platforms is a plus.
- Knowledge about Generative AI techniques – like prompt engineering, fine tuning and frameworks like Lang chain & Llama Index is a plus