Director, Data Science

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Scala Programming, R Programming, Speech recognition, 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.

If your skills reside at the intersection of analytics, technology, business and innovation, then we have a unique and exciting opportunity for you!

Prudential Financial is looking for a Data Science Director to join our diverse team of Engineers, Economists, Computer Scientists, Mathematicians, Physicists, Statisticians and Actuaries developing cutting edge solutions to complex business problems using machine learning, statistical and mathematical modeling, and advanced analytics.

The role requires a rare combination of analytical expertise; business acumen; a strategic mindset; client relationship skills; problem solving; and a passion for using advanced machine learning and statistical modeling to generate business impact. This is an exciting opportunity to be at the forefront of data science, lead teams, work on challenging business problems, and have a significant impact in transforming businesses.

Primary responsibilities for this position include leading, designing, building, testing and presenting forward-thinking, high-impact Data Science projects focused on strategic business initiatives.

Prudential Financial employs 48,000 across the US, Asia, Europe and Latin America providing insurance, investment management and other financial products that are vital to the wellbeing of our customers and their families in over 30 countries. Prudential is reinvigorating Newark’s downtown area with our new Prudential Tower and Hain building development. Newark is Prudential’s Global Headquarters with over 5,000 employees across four downtown locations. We’re located a short walk or shuttle ride from Newark’s Penn and Broad Street Stations: a direct train ride or short drive (with free parking) from most of Northern and Central New Jersey and New York City.

Responsibilities:

• Design and develop advanced statistical and machine learning models for prediction and optimization including a wide variety of machine learning technologies (logit, regression, decision trees/forests, boosted models, clustering)
• Develop relationships with business leaders and influence the adoption of data science solutions for business problems and opportunities. Build a portfolio of initiatives that drive meaningful impact.
• Build business partnerships and develop a deep understanding of the business units with which you interact. Identify opportunities to use data science to drive cost reduction, increased revenue, and improved customer experiences.
• Identify, integrate and mine large data sets, connecting data from disparate sources to identify insights and patterns using traditional as well as predictive and prescriptive analytics.
• Conduct statistical analysis using large structured and unstructured data sets (e.g., speech analytics, digital footprints, customer behavior, financial information, proprietary market research, and secondary sources) with the goal of discovering meaningful implications for business decisions.
• Identify, source, transform and join public, proprietary and internal data sources. Model large structured and unstructured data sources (financial transactional, time-series, text, speech/audio and image).
• Oversee the creation, implementation, and delivery of an end-to-end technical solution for a data science project by guiding technical staff.
• Develop and design presentations, reports, and other deliverables to communicate findings and make recommendations with a focus on “what it means” and “actions” to consider. Summarize findings in written and verbal reports to key stakeholders, communicating with technical and non-technical team members.
• Manage and mentor a team of junior staff in applying theory to practice on a day-to-day basis in business context, anticipate roadblocks, and represent the technical side of the project at all meetings.

Qualifications:

• Advanced degree (Masters or PhD) in Mathematics, Statistics, Engineering, Econometrics, Physics, Computer Science, Actuarial, Data Science, or comparable quantitative disciplines or combination of bachelor degree and demonstrated track record of developing advanced data science models for complex problems that deliver meaningful business outcomes.
• 8-10 years of relevant industry experience with responsibility for developing advanced quantitative, analytical, statistical solutions
• Hands-on experience applying a wide variety of statistical machine learning techniques to real world problems spanning analysis, predictive modeling and optimization on structured and unstructured data
• Experience using tools such as SQL, SageMaker, Python, R, or equivalent for statistical modeling of large data sets. Experience with creating and launching models in the cloud will be a plus
• Well-developed written and oral communication skills with ability to present complex statistical concepts to non-analytical stakeholders (Excel, Word and PowerPoint are a must) and story-telling capabilities articulate business value.
• Ability to influence business stakeholders and to drive adoption of data science solutions.
• Demonstrated ability to mentor and operational management of analytics staff based on project requirements, resourcing requirements, and planning dependencies as appropriate, anticipate risks and bottlenecks and proactively takes actions
• Engages with the broader project management and technology teams to facilitate timely delivery of results and outcomes
• Software engineering experience in C/C++/C#/Java/Scala or similar object oriented or functional languages is highly regarded but not a prerequisite
  M.B.A. when combined with advanced quantitative degree is highly regarded but not a prerequisite
• Prior academic or industry research experience is highly regarded but not a prerequisite
• Prior exposure to financial services or insurance industry may be helpful but is not a prerequisite