Data Engineer II Big Data & ML Analytics

As an analyst on the Data Science & Engineering team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data. Overview Responsible for developing data-driven innovative analytical solutions and identifying opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations / decisions Activities include building ML models, automated data pipelines, design data architecture/schema, perform jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc. As a Data Scientist/Engineer, you will: Drive the evolution of Data & Services products/platform with an impact focused on data science and engineering Participate in development of data and analytic infrastructure for product development Participate in identification and evaluation of data elements to deliver analytics for product development Continuously innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations Partner with roles across the organization including consultants, engineering, and sales to determine the highest priority problems to solve Evaluate trade-offs between many possible analytics solutions to a problem, taking into account usability, technical feasibility, timelines, and differing stakeholder opinions to make a decision Break large solutions into smaller, releasable milestones to collect data and feedback from product managers, clients and other stakeholders Evangelize releases to users, incorporating feedback, and tracking usage to inform future development Work with small, cross-functional teams to define vision, establish team culture and processes Consistently focus on key drivers of organization value and prioritize operational activities accordingly Identify and acts upon product improvement opportunities Aggregates and collates client data sets and conducts data manipulation and technical analysis leveraging industry techniques and best practices to identify trends and draw insights Cleans and structures data sets fed to downstream analytics Escalates technical errors or bugs detected in project work Ideal Candidate Qualifications: Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering Experience leveraging open source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses Experience developing and configuring dashboards is a plus Demonstrated judgement when escalating issues to the project team High proficiency in Python/Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL Curiosity, creativity, and excitement for technology and innovation Demonstrated quantitative and problem-solving abilities Ability to multi-task and strong attention to detail Motivation, flexibility, self-direction, and desire to thrive on small project teams Outstanding communication and organizational skills Superior academic record at a leading national university Strong English written and verbal communication skills Corporate Security Responsibility All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines. #J-18808-Ljbffr