DescriptionResponsibilities:
- 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 development best practices to code and document the solution.
Required Qualification:
- 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.
- Intermediate level knowledge of data science frameworks like Pandas NumPy & visualization libraries like Seaborn Plotly etc.
- Knowledge about Generative AI techniques like prompt engineering frameworks like Lang chain & Llama Index Evals and Agentic AI.
- Proficient in coding - Python & SQL programming
- Ability to learn and apply 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.
Required Experience:
Intern
DescriptionResponsibilities: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 cen...
DescriptionResponsibilities:
- 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 development best practices to code and document the solution.
Required Qualification:
- 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.
- Intermediate level knowledge of data science frameworks like Pandas NumPy & visualization libraries like Seaborn Plotly etc.
- Knowledge about Generative AI techniques like prompt engineering frameworks like Lang chain & Llama Index Evals and Agentic AI.
- Proficient in coding - Python & SQL programming
- Ability to learn and apply 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.
Required Experience:
Intern
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