Prudential - Data Science & Artificial Intelligence Role

Job Description

Prudential Background

Prudential plc is an international financial services group serving around 24 million insurance customers and with about - 0.6 trillion of assets under management. We are listed on stock exchanges in London, Hong Kong, Singapore and New York.

Our business: We provide protection and savings opportunities to our customers, social and economic benefits to the communities in which we operate, jobs and opportunities to our employees and long-term value for our investors.

Our strategy: Our clear and consistent strategy utilises our capabilities, footprint, and scale to serve the global savings and Asian protection needs of an increasingly self-reliant middle class to create long-term value for our customers and our shareholders.

Our performance: To create sustainable economic value for our shareholders we focus on delivering growth and cash while maintaining appropriate capital.

Our Data Science and Artificial Intelligence teams produce state-of-the-art machine learning models. In addition to pure model-building, we add Data Science capabilities to the applications we develop. At Prudential, our Data Scientists have worked on the following sample engagements:

- Building a voice-enabled customer service chatbot for our largest customer unit

- Exploring social media in selected South East Asian countries

- Building an automated record retrieval and speech analysis system

- Building a Next Best Action recommender to drive agent productivity

- Identifying fraud, waste, and abuse in healthcare claims

- Building a robot-advice pilot for one of our investment management businesses

The work will involve(but not limited to) leveraging approach :

- Machine Learning techniques (recommendation engines, ensemble models such as random forests, bagging and boosting, support vector machines, dynamic optimization etc.)

- Design and build systems that mine massive datasets and structure/ engineer it to be used for machine learning models

- Deployment of the models using web-interfacing languages such as Java, Python

- Explore and suggest AI-based solutions such as Convolutional Neural Networks

- We are looking for talented individuals to join our team - people with an empiricist attitude towards data, with mathematical intuition, curiosity, a positive outlook and who have worked on real data problems.

Role & Responsibilities :

- Apply machine learning techniques to deliver actionable insights from large-scale, multi-structured data sets.

- Work unsupervised with internal and external teams to respond to business requirements.

- End-to-end responsibility for model development, including data exploration, training data, feature extraction and model development, validation and scoring.

- Convincingly communicate with our stakeholders at all levels, including pairing with other Data Scientists.

Skills & Capabilities Summary :

- Machine Learning: Strong background in at least one specific machine learning area.

- Coding: Excellent skills in at least one procedural language (for instance, but not limited to Python, R or similar). Comfortable with command-line tools.

- Real-life experience with the tools of the Hadoop ecosystem are a plus.

- Experience with large-scale model deployment is a plus.

- Deep learning experience using one of the most popular frameworks is a plus.

Skills/Capability: Must have :

- Strong programming skills with at least one object-oriented language (e.g. Java) and one scripting language (e.g. R, Python). Conversant with advanced machine learning techniques such as Boltzmann machine as well as neural networks design and implementation through tools like tensorflow or equivalent.

- Should have at-least 2 end-to-end ML projects experience. Starting from organizing and munging data, prototyping algorithms in scripting languages to deploying a solution in a stable platform like Java.

- Database management systems and experience with handling data using SQL and ETL tools.

- Experience in working with packages such as - Generalized linear models (Lasso, Ridge, Logit), Recommendation engines (SVD, ALS, Boltzmann machine in platforms such as Mahout),Neural Networks (nnets, tensorflow),Optimization (heuristic models), Visualization techniques (t-sne, ggplot, matplotlib, shiny, D3js).

- Exposure to massive data storage architectures - Map-Reduce/ Columnar Databases/ NoSQL/ RDD-Spark

Skills/Capability: Good to have :

- Experience with distributed platforms such as Spark, Mahout, Hadoop is a plus

- Exposure to Artificial Intelligence platforms such as thaneo is a plus

- Experience with text mining/NLP would be desirable.

- Exposure to massive data storage architectures - Map-Reduce/ Columnar Databases/ NoSQL/ RDD-Spark

- Exposure to design of experiments

Experience :

- Relevant Masters degree, PhD preferred.

- At least 2+ years of real-world experience working as a Data Scientist.

Business Savvy :

- Able to communicate with non-technical business stakeholders.

- Focused on delivering value rather than technical know-how.

Personal Qualities :

- Inherently curious about data.

- Team-oriented and collaborative nature, while also able to work in a self-directed and self-motivated manner. Ability to work side-by-side all day.

- Business-oriented with a proactive focus on collaborative problem-solving.

- The desire to learn and to grow personally and professionally paired with the capability to think beyond the here and now.

- Willing and able to travel.