Data Science Role - IT/eCommerce

Responsibilities :

- Set the vision, create the roadmap, and maintain (and invest) in infrastructure-team-process.

- Set the culture and mission to attract the best team possible. Continuously refine the set of priorities for a team of Data Scientists and Data Engineers.

- Oversee the development of the technology stack that will enable data exploration and analysis including: data architecture, tagging and operational processes, data taxonomy, and reporting.

- Work with all stakeholders (marketing, operations, merchandising, finance, product design, etc.) by gathering data from all business units, developing requirements, ascertaining priorities, and reporting progress.

- Build applications, both consumer-facing and internal, so that we can collect and analyse billions of real-time data points on our products, service, and customers - and instantaneously optimize customer experience or resource utilization.

- Manage reports, create dashboards, and visualize data to communicate the delivery of information to stakeholders.

Ensure all the three phases of ETL (extract, transform, load) execute in parallel and are managed seamlessly.

- Consider important KPIs and measurements including latency, concurrency, access pattern, queries, data scope, end users, and technologies employed.

Experience in : 

- Building predictive models on and running real-time experiments against web-log scale data, natural language processing and applications of deep learning

- Experience across both data science and data engineering and ability to develop best practice and discipline for the team

- Passion for data visualisation and effective communication with data

- Experience managing and developing data science teams (or at very least, coaching junior members of a team)

Technical Toolset Knowledge :

- TensorFlow, SQL, R, big data technologies (Spark, Hadoop etc)

Requirements :

- Min 3+ years of expertise working on and managing analytics/data science teams with consumer-facing companies (ideally in the eCommerce and/or subscription space).

- Ability to both manage and recruit a team while still being hands-on.

- Fluency in R, Python, or Julia.

- Experience with relational databases / SQL.

- Experience using Dynamo, Cassandra, Hbase, or other non-relational DB.

- High skill in data visualization.

- Proven ability to set a vision of where we will be in 2-5 years and set in place the systems-level thinking to get there.

- General industry knowledge of how distributed database infrastructure has been the solution to handling some of the biggest data warehouses on the planet - i.e. the likes of Netflix, Google, Amazon, Facebook, LinkedIn, and Twitter.

- Solid understanding of the Data Scientist project lifecycle processes including: initiation, identification of data needs, methodology selection, proof of concept, release and version control, validation and experimentation, production releases, maintenance and iteration.

- Deep understanding how to extract data from homogeneous or heterogeneous data sources (ETL), and transform the data for storing it in the proper format or structure for the purposes of querying and analysis.

- Experience developing dashboards and key metrics to track the business and inform strategy.

- Comfort with ambiguity and constant change.

- A strong communication skill set to make sure your team understands the - why- behind what they are building as well as - how- they are going to measure to understand success.