The Data & Analytics Office (DAO) is responsible for enterprise-wide governance and utilization of information as an asset, via data acquisition, data processing, analysis, data mining, and other means to create value for the organization. The DAO oversees data collection, use and strategy throughout AXA. This data includes large structured and unstructured data sets (e.g., speech analytics, social media listening, digital footprints, customer behavior, financial information, proprietary market research, and secondary sources) with the goal of discovering meaningful implications for business decisions.
Director of Data Engineering, reporting to the Chief Data and Analytics Officer, will manage and direct multiple Data Engineers supporting creation of data products; analytic and business Solutions; data governance; and data quality initiatives. May also be responsible for directly handling complex exploratory data analysis. Provide support to the Chief Data and Analytic Officer for development of tactical plans to implement the company's short term and long-term data science strategy. Act as coach and mentor to Data Engineers. Work to develop Data Engineers' careers to advance in knowledge, scope of work, and / or management in the future. Perform performance reviews with direct reports. Hold weekly team meetings and one on one meetings to ensure scheduled work is on time and on scope and maintain team morale and communications. Has subject matter expert level training and knowledge to lead the team and develop best practice to explore and understand data sets; visualize the data; determine whether the data set has enough information to answer the question that the business is asking. Coordinate with IT leads and the Data Engineer team to plan and ensure funding to create ETL/ELT interfaces to the data lake and data products on the data lake; implement required data transformation in the data lake; configure or change required column level security to a data set; change or configure data masking in the data lake; investigate and resolve interface issues; work with IT to productionize models and model interfaces and business procedures for using the models. Understand AXA business and IT systems; Has deep knowledge of analytic tools, visualization tools, and analytic solutions; Lead testing of interfaces and analytic models. Investigate and provide recommendations for infrastructure and tools upgrades and new tools and solutions.
Master's Degree in Statistical Analytics, Data Science, or Actuarial Science. A Bachelor's Degree will be considered with at least six - ten years of applicable work experience.
Requires experience in managing team of data engineers or IT development teams. Requires experience independently working with coding tools such as SQL, R and Python and Hadoop experience to perform exploratory data analysis, determination of correlation and predictive capabilities of the data, development of analytic models, and work with IT on developing interfaces to the data lake. Can demonstrate a deep sense of curiosity, self-directedness and strong problem-solving skills. Has strong verbal and written communication skills.
Relevant technical skills include applied mathematics, statistics, calculus, quantitative or statistical methods or techniques, data mining, informatics, machine learning, data science, programming, computational algorithms, databases, artificial intelligence, natural language processing, Bayesian inference, Markov logic, java, software engineering and/or systems design analysis.
Relevant work experience in the following technical areas are required: Hadoop (Cloudera, Horton Works), relational databases and SQL, ETL development, spark, data validation and testing (Data Warehousing, ETL/ELT to the Data Lake, Using the Data Lake for data analysis (Hadoop tools – Hive, Impala, Pig, Sqoop, Hue, Kafka, etc., Open Source tools: Python, R, java).
Knowledge of Cloud platform implementation (Azure or Amazon).
Knowledge of data visualization tools required (AXA US uses Tableau on multiple platforms along with Python visualization in the Data Lake using Pandas and bokeh packages)
Knowledge in machine learning or statistics
IT experience coding and testing programs and utilities to transport and transform data a plus.
Knowledge and experience in working with metadata management tools a plus.
Multi-line Life Insurance and Annuity experience preferred.
Knowledge in machine learning or statistics
Knowledge of SAS and SPSS a plus.
Experience with legacy systems (i.e., mainframes), additional software development experience, project management experience and production deployment experience