Senior Data Scientist – Enterprise Corporate Functions

Key Skills

Microsoft-Excel, Java Programming, Python Programming, SQL, Data science techniques, Keras software library, Natural Language Processing (NLP), NumPy, Pandas, PyTorch, TensorFlow, Scikit-learn, matplotlib, seaborn, Powerpoint

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!

Global Technology’s Chief Data Office is looking for an experienced data scientist to join our Corporate Functions Data science team. Responsibilities will include applied research, development, and implementation of machine learning / AI solutions for multitude internal function areas, such as legal, privacy and ethics, finance, asset management, communications, etc., that are critical to enterprise operations. This individual will join a diverse and dynamic team tasked with mining our ever-increasing multidimensional internal data to create new data science products that can create actionable insights and recommendations for internal corporate functions to capitalize on. The role requires a rare combination of sophisticated analytical expertise, business acumen, strategic mindset, client relationship skills, management in Agile delivery framework, and a passion for generating business impact that will transform the company.

Responsibilities:

• Apply expertise in one or more areas, such as NLP/NLG, financial analysis and forecasting, customer interactions, large-scale internal business documents mining, etc., both from quantitative & qualitative perspective to create data science products to be deployed in enterprise setting
• Implement advanced statistical methods for prediction and optimization including a wide variety of machine learning technologies, including but not limited to, regression, decision trees/forests, boosted models, clustering, etc., for exploratory analysis, survival analysis, segmentation, prediction, forecasting, portfolio optimization, recommendation systems, and organizational network analysis.
• Be technically proficient in working with Data Science systems and tools (e.g., AWS-Athena, AWS-S3, AWS-Sagemaker, JIRA, Confluence, Bitbucket, Jenkins, Jupyter, Python, SQL).
• Identify, source, transform and join public, proprietary and internal data sources.
• Model large structured and unstructured data sources (e.g., text, speech/audio, images).
• Translate the data and your models into a compelling story that business leaders will easily be able to understand and execute on recommendations
• Communicate statistical analyses, machine learning approaches, and results, as well as implications of those efforts to technical and non-technical audiences.
• Execute all aspects of an advanced analytics under guidance of portfolio owner
• Be comfortable working within a matrixed environment where your work will be with respective corporate functions, and your reporting structure will be within Global Technology’s Chief Data Office team

Basic Qualifications:

• Master’s degree in Statistics, Economics, Mathematics, Finance, Engineering, Physics, Computer Science, Actuarial, Data Science, Business, or other related degree. Bachelor’s degree with equivalent relevant work experience will be considered.
• 2+ years of experience applying multivariate statistical methods to relevant areas preferably within industry setting
• 2+ years of experience in Python, SQL, and core data science packages such as Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, and TensorFlow/Keras/PyTorch/FastAI and variety of NLP algorithms
• 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)

Preferred Qualifications:

• Ph.D. in Statistics, Economics, Mathematics, Engineering, Finance, Physics, Computer Science, Actuarial, Data Science, Business, or other related degree.
• Prior academic or industry research experience, exposure to financial services, insurance industry, or relevant corporate functions analytics experience
• Prior experience working agile delivery model

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