- Interact with the business to understand its needs and develop use cases for analytics to support its operations.
- Lead implementation of analytic approaches. Efficiently query large volumes of data and quickly draw insights.
- Analyze historical data to identify trends and support optimal decision-making.
- Create repeatable, interpretable, dynamic, and scalable models that are seamlessly incorporated into analytics solutions, and deployable into Production for use by the business.
- Develop, validate, and deploy machine learning and predictive models/algorithms.
- Analyze large datasets to extract meaningful insights and patterns.
- Collaborate with cross-functional teams to understand business requirements and provide data-driven solutions.
- Create dashboards and reports using tools like PowerBI and Tableau to communicate findings and recommendations to stakeholders.
- Continuously monitor and refine models based on new data and feedback from clients.
- Collaborate on cross-functional project planning, business partner meetings, data prioritization meetings, etc
- Stay abreast of industry trends and advancements in data science.
Qualifications &Experience
- Bachelor's degree required in the field of data science computer science, engineering, mathematics, statistics, or related fields.
- Experience in developing machine learning/ analytical models to support business activity.
- Experience with Python or R required.
- Experience with dashboarding tools (PowerBI, Tableau).
- Ability to structure a problem, and gather supporting data using big-data technology (SQL, Python).
- Proven ability to develop and implement advanced statistical models and machine learning algorithms.
- Ability to work independently and in a team environment.
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