Company

MasterCard

Description

Our Purpose

We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team – one that makes better decisions, drives innovation and delivers better business results.

Title And Summary

Lead Data Engineer- Data Engineering & Analytics

As a Lead Data Engineer in the Data Engineering & Analytics 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.

You will have the opportunity to develop data-driven innovative analytical solutions and identify opportunities to support business and client needs in a quantitative manner and facilitate informed recommendations/decisions through activities like building and implementing ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster and cloud by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.

Your Role

Drive the evolution of Data & Services products/platforms with an impact-focused on data science and engineering.
Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
Transforming data science prototypes and applying appropriate ML algorithms and tools.
Ensuring that algorithms generate accurate user recommendations.
Turning unstructured data into useful information by auto-tagging images and text-to-speech conversions.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Developing ML algorithms to analyze huge volumes of historical data to make predictions.
Running tests, performing data analysis, and interpreting test results.
Documenting machine learning processes.
Keeping abreast of developments in machine learning.
Participate in the development of data and analytic infrastructure for product development.
Continuously innovate and determine new approaches, tools, techniques & 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.
Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
Work with small, cross-functional teams to define the vision, establish team culture and processes.
Consistently focus on key drivers of organization value and prioritize operational activities accordingly.
Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing.

Ideal Candidate Qualifications

Superior academic record in Computer Science, Data Science, Computer Engineering, Technology, mathematics, statistics or a related field or equivalent work experience
5+ years of experience as a software engineer, data engineer or machine learning engineer and with open-source tools
Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture
Solid foundation in algorithms, data structures and core computer science concepts.
In-depth technical knowledge, drive, and ability to learn new technologies.
Demonstrated basic knowledge of data analytical techniques, coding, and data engineering.
High proficiency in using Python/Spark, Hadoop platforms & tools (Hive, Impala, Airflow, NiFi), SQL to build Big Data products & platforms.
Experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Java, Scala, or Python and deliver analytics involving all phases like data ingestion, feature engineering, modeling, tuning, evaluating, monitoring, and presenting.
Curiosity, creativity, and excitement for technology and innovation.
Demonstrated quantitative and problem-solving abilities.
Experience in developing integrated cloud applications with services like Azure, Databricks, AWS or GCP.
Experience in managing/working in Agile teams.

The Following Skills Will Be Considered As a Plus

Advanced technical skills and experience of Java/JEE with Spring Framework (including Spring Boot), with successfully track record of designing, building, and supporting complex, large scale, and business critical software applications.
Experience implementing REST services.
Experience leveraging open-source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses.
Experience developing and configuring dashboards.
Experience with API development.
Financial Institution / Payments experience.

In the US, 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 reasonable_accommodation@mastercard.com 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.

Corporate Security Responsibility

Responsibilities

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.

Pay Ranges

Miami, Florida: $137,000 - $213,000 USD

Identifier

912533f0b8bfd528ac788d196b9df0d7