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 for Data Scientist Role:
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.