1. Identify opportunities to deliver business impact through data-driven solutions.
2. Prioritize solutions to be developed, delegate to team members, guide team to deliver effective analytical solutions to achieve the business impact.
3. Build effective professional network with key stakeholders to get buy-in for proposed solutions.
4. Own the design, development and maintenance of ML / statistical models and analyses.
5. Guide junior team members to apply relevant techniques of hypothesis testing, machine learning / statistical models like classification, regression and time series forecasting.
6. Take ownership to accurately measure the impact of the data science models developed.
7. Evangelize the impact of analytical solutions with multiple business stakeholders and expand solutions to more business use-cases.
8. Keep abreast of newly emerging techniques and tools in data science by participating in forums such as Kaggle, Machinehack, Github, Reddit etc.
Key Skills:
- Knowledge of and hands-on expertise with quantitative analysis techniques and tools used in statistical modeling / ML
- Business acumen paired with problem-solving ability
- Demonstrated experience in managing a team of data analysts and scientists to deliver tangible business impact
- Excellent communication and presentation skills, written and verbal
- High level of interpersonal skills to build relationships with stakeholders across the organization
- Experience with cloud data frameworks (Azure ADLS, GCP, Hadoop) is an advantage
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