Data Science Manager at Enterprise in Egham
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Data Science Manager

Job ID 293924 Egham, United Kingdom

Overview

Add an annual turnover of $24.1 billion to a fleet of 2 million vehicles spread across over 10,000 locations worldwide and you get Enterprise Rent-A-Car – the largest global mobility provider in the world.

Join us as a Data Science Manager in our European Analytic Centre of Excellence (ACE) and you will be independently leading initiatives using extensive data science expertise to understand internal and external customers' strategic business objectives. This role will also see you utilising measurable indicators to deliver analytic products and services, creating new insights and strategies promoting continuous performance improvements for the company. By applying advanced skills and expertise,developing and implementing advanced statistical and mathematical solutions, you'll be creating efficiencies and improving the decision-making process for internal business units.

Your management skills are all important too as you will be leading a newly formed team of Data Scientists by providing skills development, guidance and training.  You will be in the enviable and exciting position to actively contribute in shaping this new team's course, helping us to grow our data science practice from the ground up.

It’s no surprise that Enterprise has captured the top spot in the latest JD Power Rental Car Satisfaction Study for the fifth year in a row, even topping satisfaction scores for hotels, airlines and airports. It’s our relentless focus on providing excellent customer service that has enabled our business to grow. This is your chance to leverage the data we produce to deliver the insights and strategies that will enable us to grow that success even further.

Responsibilities

  • Design and delivery of end-to-end advanced analytical solutions that address the business needs whilst strategically linking the team's analytical activities with business goals
  • Independently extract, clean and manipulate both structured and unstructured datasets
  • Perform exploratory data analysis, generate hypotheses and extract actionable insights
  • Develop statistical and/or mathematical models that are put in production; assess current models in production and identify opportunities for enhancement and automation
  • Independently deliver detailed documentation including descriptions of efforts, results, insights and recommendations
  • Present the findings and recommendations to other ACE members and all levels of management
  • Partner with other ACE Teams to ensure successful delivery of solutions
  • Serve as an Enterprise Holdings expert in analytics and data conversations with internal customers, external customers, new business opportunities and for assigned area including but not limited to Data Quality, Modeling and Statistical Analysis, Analytical Reporting, Analytical Process
  • Management of a team of Data Scientists, with responsibility for training and employee development
  • Lead and engage ACE members as well as other parts of the organization to analyse results in order to formulate actionable recommendations
  • Manage and direct capture of business requirements, map out and define approaches, select appropriate techniques and technologies to solve problems and deliver solutions to the business that meet organizational objectives
  • Create a culture for serving as primary champions of data integrity, quality, data governance and privacy

Qualifications

  • Academic background in Mathematics, Statistics, Operations Research, Physics, Engineering, Economics, Computer Science or a related quantitative field required
  • Significant experience in the following: 
    • Data mining and developing statistical and/or mathematical models using R, Python, CPLEX, or similar
    • SQL and/or Python programming or directly querying relational databases such as Teradata, SQL Server, Oracle, or similar
    • Building statistical and/or mathematical models that are put in production
    • Preparing and giving presentations to non-technical audiences, including all levels of management
    • Applying strategic analytics within a corporate setting
    • Conceptualising new analytical products or enhancing existing products by using advanced analytical techniques
    • Guiding and mentoring other data scientists

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