Inchcape is one of the world’s largest independent automotive distributors and retailers. We manage the end-to-end distribution, logistics and customer experience for the best car brands in the world.
As a Data Scientist on Inchcape Analytics team, you’ll work on all aspects of Data Science Development helping build persuasive data science products (algorithms/use-cases) for a multi-brand automotive distributor with operations spanning countries on five continents. You’ll provide your technical expertise in guiding the successful development and deployment of data products, leveraging cutting-edge technologies that will power revenue-generating business applications and processes.
You will provide your leadership to a global cross-functional team comprising of various functions like data science, statistical analysis, automation, BI, analytics architecture, experimentation, and business analysis. You will also provide technical oversight and guidance for our acceleration partners who we’ve employed to help push forward our business objectives.
At your core, you are passionate about building and deploying analytics that unlock true, measurable incremental revenue for the business – simply producing decks and reports is not enough for you!
A career with Inchcape provides the opportunity to lead a team in a multinational business where data analytics is being put at the heart of the business strategy. You will experience in an exciting and rapidly growing team and an opportunity to be part of a truly global company.
Roles and Responsibilities:
• Use Advanced Analytics & Predictive Modelling to derive actionable insights
- Working across our global community of data scientists and engineers — and partnering closely with analytics infrastructure & data engineering teams
- You will apply Machine Learning (ML) and Deep Learning (DL) methods to interpret all types of data pertaining to automotive sector and build solutions to solve the problems Inchcape is facing.
- You are adept at all aspects of analytical modelling, including the integration of data, selection, and application of predictive modelling techniques, model validation and deployment, and work with experimentation team to help integrate the model as part of the business process through “test & learn”
- Serve as a technical guide to the team and contribute to the overall infrastructure design
• Design and develop production-ready data science solutions
- Scope, design, and implement machine-learning models to solve interesting user-cases and achieve measurable improvements
- Lead big data & analytics initiatives and greenfield projects implementations
- Lead instate A/B testing as an integral part of the pipeline when evaluating changes in the offered products and services
• Deliver measurable business value with a focus on “test & learn” methodology
- Identify trends and meaningful actions for business decisions and find avenues to improve their operations
- Track performance & derive insight from the accumulated data to create value for the business.
• Develop our advanced analytics capabilities
- Lead the development of big data capabilities as well as the coordination of cross-functional analytics for the global business
- Champion a culture of data informed decision-making, hypothesis-driven experimentation, and in doing so you will be responsible for the entire lifecycle including data collection and management
You have real-world, hands-on experience of developing and deploying impactful data science projects in a global team
- Deep understanding of business modelling and how data science informs business decisions.
- Passionate about asking and answering questions in large datasets and have a strong desire to create strategies and solutions that challenge and expand the thinking of everyone around you.
- Know how to understand and tackle loosely defined problems and come up with relevant answers and impactful insights.
- Master’s degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field or bachelor’s degree in the aforementioned fields with at least 4 years of relevant experience.
- Highly proficient and experienced in Python or PySpark or Scala and its data manipulation and machine learning libraries.
- Experience with Sales & Servicing part of the business value chain with an understanding of Salesforce is a valuable add-on.
- Experience with data processing using Spark / Databricks is a plus.
- Experience using cloud services such as Azure is a plus.
- Experience working in the automotive sector will be an advantage.
- Proven track record of working in high-performing data teams that successfully implemented advanced quantitative analyses and statistical modelling with measurable impact on business performance.
- You have 4+ years as a practicing data scientist, analyst or data/analytics engineer.
- Working on data science virtual machines on the cloud (Azure, AWS, etc.). Understanding of RESTful APIs and microservices is an advantage
- Demonstrable Kaggle / Git / analytics blogs and repos are an advantage.
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