Vice President, Principal Data Scientist - Marketing

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Scala Programming, R Programming, Large data sets

Job Description

Prudential’s Global Technology team is the spark that ignites the power of Prudential for our customers and employees worldwide. Our organization plays a critical and highly visible role in delivering customer-driven solutions across every area of the company. The Global Technology team is made up of diverse, agile-thinking, and highly-skilled professionals; we use our combined capabilities to enable the organization with innovation, speed, agility, scalability and efficiency. 

The Global Technology team takes great pride in our culture where digital transformation is built into our DNA. When you join the Global Technology organization at Prudential, you’ll unlock a challenging and impactful career – all while growing your skills and advancing your profession at one of the world’s leading financial services institutions.

Prudential’s Chief Data Office is seeking a Vice President, Principal Data Scientist to lead cross functional teams of data scientists, data engineers, and ML Engineers developing solutions to shape and accelerate the firm’s Marketing and Digital vision.

The VP Marketing Data Scientist will lead the ideation, design, development, and adoption of predictive models for Marketing, Digital and Distribution to drive business outcomes. The VP will partner with leaders within business and within the Marketing, Digital, and Distribution functions within business to identify growth opportunities, to reduce customer acquisition cost, to increase lead conversion rates, and to personalize the omnichannel customer experiences. This highly visible role will lead teams of data scientists in the development and execution of complex data science initiatives, identifying business opportunities, translating business objectives into modeling outcomes; identifying data sources for use in modeling; designing and / or selecting the optimal choice of algorithms; and integrating models with production systems in partnership with machine learning engineers on agile teams.

The successful candidate must have strong business acumen, a track record of developing large scale machine learning solutions that deliver significant business value, breadth and depth of expertise in probability, statistics and machine learning, the ability to drive business relationships, a strategic and technical mindset and the ability to lead and grow analytical teams.

Responsibilities:

• Engage with business leaders to understand challenges and identify opportunities to create Data Science solutions that will generate quantifiable business outcomes
• Lead the end-to-end execution of data science solutions (incl. incubation, discovery, design, build and maintenance)
• Partner with colleagues across the CDO, Business Leaders, and the Chief Data Scientist to:
• Build the right solution to realize the business outcomes
• Acts as the voice of the customer back to the Product Team
• Sets ambitious and clear product vision communicating ‘the story’ effectively to key stakeholders and to the CDO teams
• Capture business requirements (e.g., business objectives) and translate them into data science requirements (e.g., epics, features, MVP) and develop roadmap for delivery
• Lead the Design and evaluation of Data Science solutions including data, algorithms, path to production in an iterative way
• Partner with Finance to quantify the required investment and expected benefit for each challenge and / or opportunity and secure funding for each initiative
• Socialize the plan, facilitate demand intake, deliver solution incrementally and ensure solution adoption from business, technology, and CDO partners and other key stakeholders
• Execute periodic PI Planning to prioritize work and gain alignment on plan
• Adhere to the organization’s governance, legal, compliance, and risk policies in data and data science solutioning
• 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
• Lead the execution of the Data Science solutioning
• 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 other internal technology partners, such as cloud platform architects, control function partners, data engineers, machine-learning engineers, etc., to productionize Data Science models
• Partner with business and operational partners on the integration of models into new and / or existing work streams and processes
• Partner with Platform Owners of enterprise platforms to leverage enterprise capabilities
• Translate business problems/opportunities into technical requirements and data science specifications
• Partner within and outside CDO as to identify the data required to solve business problems / address opportunities
• 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
• 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.
• 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
• Leveraging Agile, ensure alignment of Data Science product roadmap, features, and stories
• Coordinate sprint and release plans together with the Data Science Product Owner, Scrum Master and Release Train Engineers

Skills/Qualifications:

• 10+ years of direct experience in Data Science / Advanced Analytics with at least two years of experience leading large-scale machine learning programs
• PhD in Mathematics, Statistics, Computer Science, Economics or a related field 
• Superior communication and persuasion skills; talent for storytelling, visualization and creating insights from data to deliver practical recommendations for business action
• Experience in building Marketing and Digital advanced analytical solutions to support complex strategies and real time customer experiences
• 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 
• 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
• Experience managing cross functional teams of data scientist, data architect, ML engineers and analytical professionals
• Accustomed to managing multiple teams on different projects. Experience managing projects, budgets and schedules to successful completion
• Prior experience with building custom statistical models, analyzing unstructured data, and/or machine learning highly desirable 
• Entrepreneurial spirit, persistence, and resilience; comfort with and ability to thrive on and drive change while navigating ambiguity 
• Financial services industry experience a plus