Assistant Vice President - Data Science Engineering - Python/Big Data (4-7 Yrs) Delhi (Systems/Product Software)

Essential Requirement : 1) The candidate should have experience in R, Python and big data technologies (Spark, Hadoop etc) and excellent knowledge on R and Python. 2) Full time BE/BTech from Tier1 / Tier2 institute only. 3) Must have an experience of 4 to 7 years in data science. 4) Candidates from E-commerce background will be an add-on. Job Description : - The company is one of the fastest growing big-data platform in the region looking for a phenomenal leader of Data Science to analyze massive sets of data, generate powerful insights, and create data products which directly inform our daily decisions on growth, retention, revenue, merchandising, new categories, operational efficiencies, and consumer experiences.
-The Data Science department will apply quantitative analysis, data mining, and the presentation of data to guide and steer the teams efforts to convey key product trends and opportunities. Ultimately, you will lead (and grow) the team to develop machine-learning algorithms to personalize user experience, product recommendations, and churn intervention. 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 analyze 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 visualization and effective communication with data - Experience managing and developing data science teams (or at very least, coaching junior members of a team) Requirements : - Min 4 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 of 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

Required Skills : English