Data Scientist

Position Overview

We are seeking experienced Data Scientists to add to our team to drive the next generation of Commercial Business. Data Scientists work in a Product Management Delivery model working end-to-end with business managers, product owners, product designers, data engineers, software developers to deliver next-gen analytics innovation.

This is an exciting, fast-paced role which requires exceptional organisation skills combined with strategic thinking, problem-solving and agile management tools to support team success.

As a Data Scientist Lead, you will formulate approaches to solve problems using well-defined algorithms and data sources. You will incorporate an understanding of product functionality and customer perspective to provide context for those problems. You will use data exploration techniques to Client new questions or opportunities within your problem area and propose applicability and limitations of the data. Successful Data Scientists will interpret the results of their analysis, validate their approach, and learn to monitor, analyse, and iterate to continuously improve. You will engage with peer stakeholders to produce clear, compelling, actionable output that influence product and service improvements. The form of these process will vary within Ford Pro based on the customer area, the type of technology in use, and the complexity of product integration.

Your Responsibilities (not necessarily all essential responsibilities)

Strategic Thinking: Able to influence the strategic direction of the company by identifying opportunities in large, rich data sets and creating and implementing data driven strategies that fuel growth including cost savings, revenue, and profit.

Modelling: Assessments and evaluating impacts of missing/unusable data; design and select features, develop, and implement statistical models using edge algorithms on diverse sources of data and testing and validation of models.

Analytics: Utilise analytical applications like Python, R, Alteryx, ArcGIS to identify trends and relationships between different pieces of data, draw appropriate conclusions and translate analytical findings into business strategies or analytics software.

Data Engineering: Experience with creating ETL processes to source and link data in preparation for Model/Algorithm development. This includes domain expertise of data sets in the environment, third-party data evaluations, data quality.

Visualisation: Create visualisations to connect disparate data, find patterns and tell engaging stories. This includes both scientific visualisation as well as geographic using applications such as QlikSense or ArcGIS.

Minimum Qualifications

• Bachelor’s Degree in Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, Operations Research, Computer Science, Information Technology, or in any of the physical or biological sciences with strong curriculum in data analytics.

• 2+ years of experience of statistical methods and their proper application e.g., principle component analysis / factor analysis, correspondence analysis, k-means cluster analysis, multi-variate analysis, linear regressions, non-linear regressions, time-series econometrics.

• 2+ years of experience using statistical and data querying software (e.g., Python, R, Spark, SQL, SAS, SPSS, STATA, Alteryx).

• Experience working in a cross-functional, agile product team environment/analytic delivery team.

• 1+ years executive presentation preparation and delivery.

• 2+ years of experience using MS-Office (Excel, PowerPoint).

• Preferred Skills

• Master’s Degree in Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, Operations Research, IT, or in any of the physical or biological sciences with strong curriculum in data analytics.

Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, Support Vector Machines, Interaction Effects, Importance modelling, machine learning, regression, image processing, natural language processing, control charting, linear or mixed integer optimisation.

Expertise in open source data science technologies such as Python, R, Spark, SQL, Hadoop, etc. acquired through college course work, online training and certification or project development.

Demonstrated expertise in commercial tools such as Alteryx, QlikView, and Tableau acquired through training and/or implementation on projects.

Experience with designing, developing, and operationalising Machine Learning models.

Familiarity working with big data to develop scalable, production-ready solutions.

Experience working with non-Data Scientists – Data Engineers, Software Engineers, Designers.

Self-motivated with excellent verbal and written skills.

Proactive, great attention to details, results-oriented problem-solver.

Ability to work under pressure, establish priorities and respond with urgency.

Consensus building and collaborative interpersonal skills – ability to work with Ford enterprise-wide data, analytics, and IT product teams located in the UK, US, Germany, and India on adapting analysis tools to the European market.

Highly seasoned in organisational, time management, decision making and problem-solving skills.

Other Considerations and Information

· It is expected that this role will involve a hybrid and flexible working model, i.e. most days you are likely to work from home, with an expectation to come to the office 1-2 days a week. In certain cases, we could consider candidates based relatively far from one of the Ford offices, if they are willing to commute to the office circa 2-3 times a month.

· Possible Ford home office locations – preferences to be discussed during the interview:

· UK (preferred) – Stratford, London or Dunton, Essex.

· Willing to travel occasionally to other locations (e.g., Germany, UK, USA).

· Candidate applications with cover-letter introductions have preferred consideration

Job type: Contract Division: eTeam Workforce Limited Reference: 21-04993