Manager, ML Engineer
Full Time
Others
Job 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
Manager, ML Engineer
As the Manager of the Data Science & Engineering team, you will develop data products and 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 machine learning techniques including deep learning, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses with a keen eye for data privacy. 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 ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.
As a ML Engineer, you will:
- Drive the evolution of Data & Services products/platforms with an impact focused on ML and engineering
- Design machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
- Participate in identification and evaluation of data elements to deliver analytics for product development
- Solve complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
- Continuously innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations
- Participate in the development of data and analytic infrastructure for product development
- 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
- Escalate technical errors or bugs detected in project work
- Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations
- Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
- Maintain awareness of relevant industry-standard technical and product trends
- Provide excellent leadership of team members through technical and non-technical mentoring and superior project management over the course of multiple complex assignments
Ideal Candidate Qualifications:
- 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, modelling, tuning, evaluating, monitoring, and presenting
- High proficiency in Python, Spark, SQL
- Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark)
- Motivated, flexible, self-directed, and desire to lead small project teams
- Curiosity, creativity, and excitement for technology and innovation
- Demonstrated quantitative and problem-solving abilities
- Strong project management skills
- Ability to multi-task and strong attention to detail
- Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement
- Flexibility to work as a member of a matrix based diverse and geographically distributed project teams
- Outstanding communication and organizational skills
- Experience as a people manager
The following skills will be a plus:
- Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts
- Batch processing and workflow tools such as NiFi
- Experience in managing/working in Agile teams
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:
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
Manager, ML Engineer
As the Manager of the Data Science & Engineering team, you will develop data products and 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 machine learning techniques including deep learning, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses with a keen eye for data privacy. 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 ML models, automated data pipelines, designing data architecture/schema, performing jobs in big data cluster by using different execution engines and program languages such as Hive/Impala, Python, Spark, R, etc.
As a ML Engineer, you will:
- Drive the evolution of Data & Services products/platforms with an impact focused on ML and engineering
- Design machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
- Participate in identification and evaluation of data elements to deliver analytics for product development
- Solve complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
- Continuously innovate and determine new approaches & technologies to solve business problems and generate business insights & recommendations
- Participate in the development of data and analytic infrastructure for product development
- 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
- Escalate technical errors or bugs detected in project work
- Continuously innovate and determine new approaches, tools, techniques & technologies to solve business problems and generate business insights & recommendations
- Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
- Maintain awareness of relevant industry-standard technical and product trends
- Provide excellent leadership of team members through technical and non-technical mentoring and superior project management over the course of multiple complex assignments
Ideal Candidate Qualifications:
- 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, modelling, tuning, evaluating, monitoring, and presenting
- High proficiency in Python, Spark, SQL
- Preferably with hands-on experience with Hadoop big data tools (Hive, Impala, Spark)
- Motivated, flexible, self-directed, and desire to lead small project teams
- Curiosity, creativity, and excitement for technology and innovation
- Demonstrated quantitative and problem-solving abilities
- Strong project management skills
- Ability to multi-task and strong attention to detail
- Ability to quickly learn and implement new technologies, and perform POC to explore best solution for the problem statement
- Flexibility to work as a member of a matrix based diverse and geographically distributed project teams
- Outstanding communication and organizational skills
- Experience as a people manager
The following skills will be a plus:
- Experience with performance Tuning of Database Schemas, Databases, SQL, ETL Jobs, and related scripts
- Batch processing and workflow tools such as NiFi
- Experience in managing/working in Agile teams
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.
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