What are the responsibilities and job description for the Sr. Data Scientist (Operations) position at Karkidi?
As the Senior Data Scientist, you will lead initiatives targeted to drive efficiency, scalability, and operational performance using AI / ML. In this role, you will source, manage, and analyze large volumes of structured and unstructured data, synthesize results, and communicate / collaborate on the results with key stakeholders to drive strategic decision making in the organization.
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This role will require heavy collaboration across other data science, engineering, and analytics teams while also acting as an individual contributor as Operations build out Data Science skills and abilities. The ideal candidate will be deeply immersed in data science with hands-on modeling experience, driven by a passion for uncovering insights that fuel Prosper's growth and customer strategies. This role will be heavily invested in financial operations, particularly collections but inclusive of loan verifications, customer servicing, sales strategy, complaints, and customer experience. You will serve as subject matter expert on AI / ML in Operations and eventually cultivate a team of Data Scientists to deepen our strength in this space.
Problems You Will Solve
- Responsible for the design and development of AI / ML solutions in Operations. Spearhead innovation and application development to automate / optimize current workflow and process for efficiency enhancement. Ensure the end-to-end solution meets all technical and business requirements.
- Develop creative ways to find and use data that significantly impact our key business metrics.
- Independently create proposals and identify opportunities to drive efficiency in operational processes and AI / ML.
- Design and execute tests having clear success metrics, be able to provide synthesized analysis of the results and manage solutions into production.
- Work cross functionally to shepherd projects from ideation into production working across Legal, Risk, Ops Teams, Product, Engineering to ensure efficiency.
- Develop and maintain procedures for tracking data sources, data lineage, data quality, completeness, redundancy vs replication, data dictionary, data models, metadata and master data.
- Build production models used to generate ‘next best action’ strategies across customer journeys in Collections and Sales.
- Own operations priorities and roadmap, acting as liaison across all products and functional areas to deliver AI solutions for the organization. AI solutions could include, but not limited to, analytical deployments / proofs of concept, engineering developed AI solutions, and external AI service providers.
- Continuously develop and demonstrate improved modeling methodologies; advise on best practices and methods for evaluating and measuring experiments.
- Assess the potential usefulness and validity of new statistical approaches and data sources.
About You
What We Offer
146,000 - $179,000 a year
J-18808-Ljbffr
Salary : $146,000 - $179,000
