Sr. Data Scientist

ID
2020-12700
Category
Engineering
Position Type
Full Time
Location : Location
IN-KA-Bengaluru

About Blackhawk Network:

At Blackhawk Network, we shape the future of global branded payments through the prepaid products, technologies, and networks that connect brands and people. Our collaborative innovation and scalable, security-minded solutions help our partners to increase reach, loyalty, and revenue. We believe our future holds great things for Blackhawk Network and its partners. We believe that together, we can shape the future. Our beliefs? Win as one team, be innovative, global excellence and be inspiring!

So, what are you waiting for? Shape your career and join our global network.

Overview:

What’s in it for you?

 

You will build large scale data lake that collect, processes and transforms the data into valuable business insights. You will tame all facets of big data at a Global scale and turn the wild west of data into robust and accurate business insights. The data platform that you build will enable the culture of data driven decision making across the entire company and will work at the forefront of cutting-edge technologies of data processing, visualization, and business intelligence.

 

We are looking for a trailblazer & practitioner Data Scientist to lead the initiatives we’re taking, to improve the product offerings of Blackhawk Network, from the perspective of risk modelling and business forecasting (prescriptive & predictive).

Responsibilities:

As a Senior Data Scientist, you will own the research charter for Data & Decision Science, to enable the business stakeholders to be data-driven and deterministic, by providing insights into the decisions at-hand and also roadmap planning.

 

You will be the Senior member in a team of Data Scientists to provide mentorship and enable a culture of 360-degree analysis of business, with ownership of the Modelling Environments and Risk Engines. You will get the support to evangelise sound practices for prototyping of concepts, to fail-fast and/or maintain continuum of persistent research.

 

You will collaborate with multi-disciplinary teams of engineers, product owners & business stakeholders to solve complex & ambiguous problems, in the domains of:

  1. Gift Cards E-Commerce (B2B & B2C)
  2. Forecasting of Inventory, Traffic & Breakage
  3. Risk Modelling (Scorecards)
  4. Fraud Detection & Prevention
  5. Loyalty & Rewards Programs Modelling

 

 

Qualifications:

  • A strong background in advanced mathematics, in particular statistics & probability theory, data mining, and machine learning.
  • 10+ years of overall professional experience, with 5+ years in data science, doing exploratory data analysis, testing hypotheses, and building prescriptive & predictive models.
  • Masters (or equivalent) degree in a quantitative discipline (Statistics, Operations Research, Data Science, Mathematics, Physics, Engineering etc.).
  • Proficiency in a programming language of your own choice (Python, R, Matlab, etc.), and previous experience efficiently conducting research and creating on-demand reports.
  • Strong Communication: ability to articulate clearly, navigate & adapt across different seniority levels.
  • Ability to use statistical, algorithmic, data mining, and visualization techniques to model complex problems, find opportunities, discover solutions, and deliver actionable business insights.
  • An excellent ability to learn new programming languages quickly and optimally.
  • Be passionate about collaborating daily with your team and other groups while working via a distributed multi-geo global operating model.
  • Be eager to help your teammates, share your knowledge with them, and learn from them.
  • Ability to work with large, complex data sets to produce insights & results.
  • Big pluses include significant experience managing or shipping out a product, leading a team, and working on open source projects.

#GLDR

#D18

Options:

Sorry the Share function is not working properly at this moment. Please refresh the page and try again later.
Share on your newsfeed