Head of Data Science
FarePilot(www.FarePilot.com) is a geographical recommendations app, powered by machine learning. We assist drivers find customers faster based on their location, linking to Google Maps and Waze to get them there in the most intelligent and efficient manner.
Our app uses live information about where the busiest places are (along with some clever maths) and by going to the places shown the driver should be able to get more 'pings', more often, and spend less time waiting for their next customer. The current team size is just over 20 people including both technical and commercial experts (designers, developers, engineers, product managers, data scientists, marketers and business operations).
We are seeking strong candidates with advanced analytics experience to lead our Data Science team at FarePilot. The role provides an opportunity to design and build analytics methodologies, solutions, and products to deliver extraordinary value to FarePilot users in collaboration with software engineers, designers and product managers.
Exceptional candidates will show an analytical curiosity going beyond the immediate requirements of the venture to find deep insights that others have missed. They will ask questions about outliers, seek to understand the fundamental drivers of advantage and look for clues that may change the basis of competition. As the field of advanced analytics is rapidly evolving, all members of the FarePilot team are responsible for staying current on leading-edge business applications, tools and approaches, proactively working with the leadership to enhance offerings that deliver competitive advantage to FarePilot. FarePilot is a fast-paced, intellectually intense and highly service-oriented work environment. Our current location is London.
RESPONSIBILITIES The Head of Data Scientist (HDS) will be involved in all aspects of advanced analytics, from helping to create relevant analysis and service offerings by leading and executing analytics work and continuing to expand the analytical foundation and competitive value proposition. The HDS will collaborate directly with the management and wider venture team and will manage the analytics components. The HDS is responsible for clarifying initial objectives, setting up analytics work plan and methodology, organizing the data scientist members of the team, quality assurance, and managing scope and work planning throughout the project. The HDS is expected to provide mentoring, coaching, and career development to Junior Data Scientists on both a formal and informal basis.
Education & Experience
•Degree in a field linked to computer science, applied mathematics, statistics, machine learning, or related data centric areas, or
•Relevant work experience of 5+ years
•Passion for and interest in data science topics
•Autonomous self-starter, drive and energy, and desire to work in a Start-up environment
•Creative, yet structured problem solver
•Able to work in a fast-paced environment and to manage multiple tasks in parallel
•Strong interpersonal credibility, reliability, and service mentality
•Highest ethical standards, able to maintain discretion and confidentiality
•Experience in the following analytics methods (two or more of the following):
oMachine learning: e.g. Random Forest, neural networks
oPredictive modeling: e.g. logistic regression, linear regression
oGeographic Analysis (location-allocation, travelling sales person, vehicle routing problem)
•Stong candidates additionally have experience with one or more of the following methods:
oGeographic cluster recognition and manipulation techniques oStatistics (t-tests, ANOVA)
oVariable reduction (FA, PCA)
oTime series analysis: e.g. ARIMA, VAR, etc.
oText mining & unstructured data analytics
oOptimization, e.g. linear programming, heuristic approaches
•Familiarity with a broad base of analytics tools – preferably one or more per category:
oData management, e.g. Alteryx, Excel, SQL, PostGRESql, or similar
oAnalytics platforms and languages, e.g. R, Python, RapidMiner, SPSS, or similar
oData visualization, e.g. Tableau, Qlik, or similar
oGeographic information system (GIS): ESRI incl. Network Analyst, Quantum GIS, MapInfo, or similar
•Preferably experience in applied analytics for business problem solving/experience building analytical solutions (as a plus)
oDelivery fleet optimization
oLoyalty program effectiveness
oCustomer segmentation and targeting