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Vice President, Principal Data Scientist - Marketing
Company | Prudential Financial |
Address | Newark, NJ, United States |
Employment type | FULL_TIME |
Salary | |
Category | Financial Services |
Expires | 2023-07-25 |
Posted at | 10 months ago |
Job Classification:
- Translate business problems/opportunities into technical requirements and data science specifications
- Sets ambitious and clear product vision communicating ‘the story’ effectively to key stakeholders and to the CDO teams
- Engage with business leaders to understand challenges and identify opportunities to create Data Science solutions that will generate quantifiable business outcomes
- Partner with business and operational partners on the integration of models into new and / or existing work streams and processes
- Adhere to the organization’s governance, legal, compliance, and risk policies in data and data science solutioning
- Partner with Finance to quantify the required investment and expected benefit for each challenge and / or opportunity and secure funding for each initiative
- Day-to-day operational leadership in the analysis of the data, identify algorithms capable of systematically architecting the solution, development, training, and testing of the algorithms. Consult with other Data Science leaders and CDO colleagues
- Execute periodic PI Planning to prioritize work and gain alignment on plan
- Coordinate sprint and release plans together with the Data Science Product Owner, Scrum Master and Release Train Engineers
- Acts as the voice of the customer back to the Product Team
- Capture business requirements (e.g., business objectives) and translate them into data science requirements (e.g., epics, features, MVP) and develop roadmap for delivery
- Partner within and outside CDO as to identify the data required to solve business problems / address opportunities
- Lead the execution of the Data Science solutioning
- Lead the end-to-end execution of data science solutions (incl. incubation, discovery, design, build and maintenance)
- Rigorously test multiple machine-learning algorithms using the testing framework established and select the best performing model using established criteria. Consult with other Data Science leaders and CDO colleagues in model selection. Set and evaluate model performance metrics post-production as well as service level requirements
- Partner with colleagues across the CDO, Business Leaders, and the Chief Data Scientist to:
- Build the right solution to realize the business outcomes
- Lead the Design and evaluation of Data Science solutions including data, algorithms, path to production in an iterative way
- Establish the optimal set of metrics for evaluating model performance relative to the business problem / opportunity addressed. Identify risks associated with potential algorithms. Understand and communicate the strengths and weaknesses of potential algorithms to all partners and stakeholders.
- Socialize the plan, facilitate demand intake, deliver solution incrementally and ensure solution adoption from business, technology, and CDO partners and other key stakeholders
- Manage and mentor a team of Data Scientists in the design, development, evaluation, testing, and production of data science models that deliver targeted outcomes
- Partner with Platform Owners of enterprise platforms to leverage enterprise capabilities
- Partner with other internal technology partners, such as cloud platform architects, control function partners, data engineers, machine-learning engineers, etc., to productionize Data Science models
- Be a change ambassador who exhibits tech-forward and customer-obsessed principles in co-creating data-driven advanced analytics solutions that deliver on strategic priorities
- Leveraging Agile, ensure alignment of Data Science product roadmap, features, and stories
- Accustomed to managing multiple teams on different projects. Experience managing projects, budgets and schedules to successful completion
- 10+ years of direct experience in Data Science / Advanced Analytics with at least two years of experience leading large-scale machine learning programs
- Track record of using advanced statistical modeling and machine learning to drive significant cost savings and / or incremental revenue for large enterprises, preferably in the insurance industry
- Experience managing cross functional teams of data scientist, data architect, ML engineers and analytical professionals
- PhD in Mathematics, Statistics, Computer Science, Economics or a related field
- Financial services industry experience a plus
- Prior experience with building custom statistical models, analyzing unstructured data, and/or machine learning highly desirable
- Consultative nature, with a proven track record of using data to provide actionable business results
- Proven relationship building and collaboration skills; ability to influence and drive outcomes in large, matrixed and complex organizations
- Entrepreneurial spirit, persistence, and resilience; comfort with and ability to thrive on and drive change while navigating ambiguity
- Experience in building Marketing and Digital advanced analytical solutions to support complex strategies and real time customer experiences
- Superior communication and persuasion skills; talent for storytelling, visualization and creating insights from data to deliver practical recommendations for business action
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