OLA - Lead - Data Sciences (10-15 yrs)
Roles and Responsibilities:
- Lead data science charter for OLA
- Work with product and business team to articulate business problems and use appropriate machine learning techniques to arrive at an answer using available data.
- Apply expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our consumers & customers interact with our platform, categories & product offerings. .
- Proactively drive the vision for product analytics across a product vertical, and define and execute on a plan that achieves that vision.
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Inform, influence, support, and execute our product decisions.
- Drive data quality across the product vertical and related business areas.
- Manage the delivery of high impact dashboards and data visualizations.
- Define and manage SLA's for all data sets and processes running in production.
- Manage development of data resources, gather requirements, organize sources, and support product launches.
Experience & Skills :
- The company is looking for an experienced professional who will fit in with the organization's fast-paced and - quick response time- culture.
- 10+ years of experience in managing other team members in a formal or informal capacity, with experience scaling and managing 10+ person teams.
- 8+ years of experience doing quantitative analysis.
- 8+ years of experience in an analytical role in a technology company, consulting, investment banking, or product management.
- 5+ years of experience with SQL or other programming languages.
- Experience initiating and driving projects to completion with minimal guidance.
- Communication and leadership experience.
- NoSQL paradigms, Graph databases
- Handling real time data streaming
- Statistical methods and data modelling for trends, forecasting and predictive analysis. large data sets and distributed computing (Hive/Hadoop) and data visualization tools.
Preferred Qualification :
- Advanced degree in Computer Science, Math, Physics, Engineering, or related quantitative field or MBA.
Experience in companies that are in the startup space.
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