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Data Science Manager

Axa Life Insurance

Posted on March 3, 2018

4 - 5 years United Arab Emirates - United Arab Emirates

Ph.D/Doctorate(Other). Any Nationality

Opening 01

Job Description

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We are convinced that Data Science is a key pillar of our strategy to become a more customer centric company, designing insurance solutions that enable our customers to live better lives. In line with this, AXA Gulf aims to build on and go beyond its past successes in this area through a reinforced focus on unlocking the value that data analytics can bring to our business.
Developing and strengthening the Data Science team within the organization is essential for us to reach this ambition. As a Senior Data Science Manager, you will report to the Director for Transformation and Data Analytics. Your role will include the management of the Data Science team, interfacing with senior business stakeholders, and delivering Data Science projects and solutions across different Business Lines and parts of the insurance value chain. Your main mission will be to translate business challenges and/or opportunities into Data Science problems to which you can apply your own skills as well as those of the team and manage the delivery and implementation of these solutions.
You will be successful in this role not only through building on and developing your subject matter expertise in Data Science techniques, but also through working closely and collaboratively with the business. This will be key to understand how to best identify domains where Data Science can help improve performance and to develop and implement solutions that are practical and adopted by the relevant business stakeholders.
Data strategy and priorities:
•Lead the Data Science team s work to build and promote strategic data assets for the business in domains covering sales and marketing, offering development, pricing, claims management, etc.
•Act as the main Data Science contributor to the innovation process and champion Data Science s role in the same
•Lead the team s work with the business, aiming at defining relevant Data Science problems that, if solved and their solutions implemented, would have a strong positive value impact
Business modeling and data transparency:
• Define relevant metrics for the Data Science team and oversee the development and maintenance of dashboards for the Data Science activity while contributing to business data reporting improvements in other areas
• Develop an excellent understanding for business needs (actuarial, sales, processing, etc.) through engagement and collaboration with various business teams (sales, offering and product development, actuarial, etc.)
• Coordinate and quality-proof the Data Science team s project work, models, and solutions including overseeing their collaboration with IT on securing models and solutions performance over time
• Plan for and secure scalability of delivered solutions and future use cases through close collaboration with IT product teams
• Ensure the creation and use of impact assessment models, together with relevant business and Finance teams, for all Data Science initiatives and/or developments
•Encourage and coordinate team members exploratory analyses on databases (including vast databases, unstructured or open, which are big data-like) to establish relations and/or correlations to potentially exploit in order to enhance business performance
Problem solving:
• Secure strong understanding of business needs, problem formalization, and overview of theoretical solutions based on available tools
• Engage with business stakeholders to establish what potential solutions would be relevant, applicable, and impactful from their perspective
• Guide the team in their choice of relevant Data Science technique(s), data processing solutions, and/or end-user output (including interface solutions) that would allow to best address the needs
• Good understanding of the insurance sector and/or other Financial Services sector and/or practical experience in applying Data Science techniques in business contexts (e.g., customer segmentation and targeting, network optimization, etc.)
Project management:
•Ensure buy-in from business stakeholders at key moments of Data Science initiatives/ projects
• Secure strong end-to-end Data Science project management, through directly managing projects and overseeing team members project management, including but not limited to:
• Business requirement sourcing, project scoping, definition of approach, time and resource planning, business case development, team onboarding, pilot delivery and evaluation (e.g., a | b testing), ramp-up of solutions, planning and enablement of production hand-over for BAU integration, etc.
•Work with senior managers across departments (e.g., Business Lines, Actuarial, IT, Finance, etc.) throughout project deliveries as relevant and pertinent, in order to facilitate model/ solution/ project delivery on time, to specifications, and at quality securing upstream that these are usable and downstream that these are used by business teams
•Secure solid knowledge management and transfer, from the Data Science team to the business, through appropriate documentation and initiatives including but not limited to:
•Efficient and effective communication on projects, solutions, and Data Science opportunities (e.g., through compelling presentations and/or documentation); solid understanding for how to best handle and communicate sensitive information; etc.
•Present and promote the delivered solutions vis- -vis relevant stakeholders and senior management


IT Software

Desired Candidate Profile

Our preferred candidate is a good people and project manager with strong technical skills, collaborative, curious, and pragmatic
Technical skills:
•Scientific education at Master level in engineering, actuarial science, or other quantitative field
• In-depth understanding of the scientific method
• Ability to formalize the business reality into equations and models, accounting for the implications and limitations of a given model
• Strong programming skills, including in Python (mandatory) and R (beneficial)
• Good knowledge of machine learning, including libraries (e.g., scikit-learn, Spark MLlib, Caret, etc.) professional experience with machine learning applied to business contexts constitutes a substantial advantage
• Experience with a Hadoop Cluster, ideally having leveraged a modern distributed computing framework (e.g., Spark)
• Strong track-record in data processing (e.g., data mining, social network analysis, text mining, etc.)
• Great ease in working with data visualization/ data tools (e.g., Matplotlib, plot.ly, C3.js, Tableau, Highcharts, Dataiku, etc.)
• Additional elements that constitute an advantage:
• Practical experience with tools such as Kafka, Rabbitmq, Redis, Riak, etc.
• Knowledge of front-end development, including but not limited to knowledge of a good javascript framework such as Angular JS
• PhD in a relevant field
• Good knowledge of Java/ Scala
Soft skills:
• Autonomy, curiosity, and eagerness to solve problems
• Capacity to perform well in a multi-cultural environment
• Excellent stakeholder management and negotiation skills
• Strong communication skills
• Ability to lead a team of Data Scientists in a way so that they continuously develop their subject matter expertise and apply the same to bring strong positive value to the business
• Strong people management skills including mentoring, people development, and motivation
• Agile mindset and working style, adapting with ease to changing requirements
• Results-oriented, hands-on, collaborative, and pragmatic focusing on managing projects well in order to deliver value uplift to the business
• Ability to work in a multi-disciplinary team, on complex topics, involving different stakeholders
• Interest in and capacity to transfer knowledge to the team and other business stakeholders
• Full fluency in English, both written and spoken, is mandatory
Experience :
• Minimum 4 years of successful professional experience as s Data Scientist, ideally within an insurance and/or other Financial Services company
• Work experience in an international environment constitutes an advantage


Project management Python Agile Data mining Front end Financial services Machine learning Tools Project delivery Knowledge management


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