Director, Data Scientist, B2B VAS
Who is Mastercard?
We are the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless ®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Job Title
Director, Data Scientist, B2B VAS
We are looking for a sharp, thoughtful analytical problem solver and leader to drive data-driven initiatives and build the analytical framework to support and advance MA goals. The Data Scientist/Strategist must love data, mission-driven opportunities and solving challenging problems in a fast paced environment. The Data Scientist/ Strategist should also have extremely strong analytical, leadership, communication and organizational skills with a strong attention to detail and a sophisticated understanding of what data means and how we can use it to make change and take actionable insights.
-Are you happiest when you're applying your technical knowledge to create novel solutions and algorithms?
-Would you like to build using the best cloud and DS tools, while also getting opportunities to do model and solution design?
-Are you looking for an opportunity to join, lead, grow and shape a high-performing, well-supported Data Science team?
-Do you hope to build a reputation as a leader in your field?
Build data partnerships with other organizations as well as 3rd party vendors.
Identify, conceptualize and lead a range of insights, predictive modeling and data science projects.
Extract, create, and organize data files used for analytical and modeling purposes.
Identify valuable data sources and automate collection processes
Undertake preprocessing of structured and unstructured data
Analyze large amounts of information to discover trends and patterns
Build predictive models and machine-learning algorithms
Combine models through ensemble modeling
Present information using data visualization techniques
Propose solutions and strategies to business challenges
Collaborate with engineering and product development teams
This role requires an individual who is highly strategic and analytic, who understands data, can collaborate across business teams and can communicate complex concepts to various business and technical teams.
The responsibilities of this individual are as follows:
Apply your strong ML background to design and implement novel algorithms and model architectures.
Partner with development teams and solution architects to identify opportunities in data capture, model iteration and new service creation.
Demonstrating value via innovative analytics
Partner with product, privacy and market development teams to identify relevant products, sites, apps and data systems, define work required for compliance with this data rights program and, implement solutions to completion
Enable the development of data-based products and solutions for the regions, while identifying information asset requirements
Understand the regions business strategy and data needs for both new and existing products and services across various B2B product initiatives within the respective regions
Identify data-related process, quality, policy and infrastructure requirements resulting from new and evolving product constructs
All About You
Proven record of delivering complex enterprise-wide large scale projects
Exceptional interpersonal skills with proven experience in relationship building and partnering. Must work well in both team and individual settings and must be able to work with a geographically dispersed team
Experience in data product development
Ability to create strategies and plans that define how data can be utilized to support an organization's overall business strategy
Familiarity with industry best practices for collection and use of data
Proven experience as a Data Scientist or Data Analyst
Experience in data mining
Understanding of machine-learning and operations research
Knowledge of R, SQL and Python; familiarity with Scala, Java or C++ is an asset
Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
Analytical mind and business acumen
Strong math skills (e.g. statistics, algebra)
Excellent communication and presentation skills
BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative field is preferred
Previous successful experience in analytics, data science and/or business intelligence with increasing responsibility.
Proven ability to synthesize and tell the story behind the data.
Familiar with statistical modeling, such as regression analysis, forecasting etc.
Proven success with translating a business problem into a data solution design of varying complexities.
Thrilled with challenges, unknowns and opportunity to define and build things.
Ideally, you are:
-Experienced in running data science projects, including project planning and calling plays during development.
-A machine learning expert with strong formal knowledge and experience applying ML in business contexts. You can identify multiple solutions for a specific problem and reason about the best options.
-Thoughtful. You support your claims with evidence or robust reasoning and are able to make forward-thinking, risk-minimizing decisions in complex operating environments.
Mastercard is an inclusive Equal Employment Opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
If you require accommodations or assistance to complete the online application process, please contact firstname.lastname@example.org and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.