Data Scientist

• Company AXA Gulf
• No. of Openings 10+
• Salary Not Disclosed
• Work Type remote

Job Description :

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 reinforcement of its Data Science team.

Securing strong Data Scientists within the organization is essential for us to reach this ambition. As a Data Scientist, you will report to the Lead Data Scientist. Your role will be versatile, covering different Business Lines and parts of the insurance value chain. Your main mission will be to deploy your strong technical expertise in both enhancing the data strategy and delivering solutions to business challenges.

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 solutions that are practical and adopted by the relevant business stakeholders.

Key Responsibilities:

Data strategy and priorities:

• Build and promote strategic data assets for the business in domains covering sales and marketing, offering development, pricing, claims management, etc.
• Contribute to the innovation process within the Data Science domain and champion business innovations linked to the same
• Translate business ambition and needs into Data Science problems to be solved

Business modeling and data transparency:

• Build, implement, and update relevant metrics and dashboards for the Data Science activity while contributing to business data reporting improvements in other areas
• Develop a good understanding for business needs (actuarial, sales, processing, etc.) through engagement and collaboration with various business teams (sales, offering and product development, actuarial, etc.)
• Translate business needs into formalized mathematical problems and models
• Contribute to the creation of impact assessment models, together with relevant business and Finance teams, for Data Science initiatives and/or developments
• Conduct 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 adequate 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
• Choose the relevant Data Science technique(s), data processing solutions, and/or end-user output (including interface solutions) that would allow to best address the needs
• Ensure buy-in from business stakeholders at key moments of Data Science initiatives/ projects
• Present and promote the delivered solutions vis-à-vis relevant stakeholders and management
• Manage and transmit the knowledge through appropriate documentation and initiatives (including training material, live demonstrations, training courses, etc.)
• 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.)

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
• Experience with AWS datalake stack, in particular SageMaker
• Strong programming skills, including in Python (mandatory) and R (mandatory)
• 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
• Strong track-record in data processing (e.g., data mining, social network analysis, text mining, etc.)
• Experience with database access (SQL and/or Pig and Hive), including NoSQL databases (e.g., Elasticsearch, MongoDB, CouchDB, JSON files, etc.)
• Great ease in working with data visualization/ data tools (e.g., QuickSight, Matplotlib, plot.ly, etc.)
• Experience delivering solutions in R Shiny and/or Flask
• 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 in a multi-cultural environment
• Good inter-personal and communication skills
• Agile mindset and working style, adapting with ease to changing requirements
• Results-oriented, hands-on, collaborative, and pragmatic – focusing on delivering value 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 2 years of successful professional experience as Data Scientist, ideally within an insurance and/or other Financial Services company
• Work experience in an international environment constitutes an advantage