Master Card Hiring : Data / ML Engineer-4
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Eligibility:
· Qualification: Any Graduate (All Education Certificates are mandatory before Joining)
Your Role
• Drive the evolution of Data & Services products/platforms with an impact-focused on data science and engineering.
• 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.
• Provide support for deployed data applications and analytical models by being a trusted advisor to Data Scientists and other data consumers by identifying data problems and guiding issue resolution with partner Data Engineers and source data providers.
• Ensure proper data governance policies are followed by implementing or validating Data Lineage, Quality checks, classification, etc.
• Discover, ingest, and incorporate new sources of real-time, streaming, batch, and API-based data into our platform to enhance the insights we get from running tests and expand the ways and properties on which we can test Experiment with new tools to streamline the development, testing, deployment, and running of our data pipelines.
• Maintain awareness of relevant technical and product trends through self-learning/study, training classes and job shadowing.
• 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
• Escalate technical errors or bugs detected in project work
• Maintain awareness of relevant technical and product trends through self-learning/study, training classes, and job shadowing.
• Support the building of scaled machine learning production systems by designing pipelines and engineering infrastructure.
Ideal Candidate Qualifications:
• Experience and exposure to Python/Scala, Spark(tuning jobs), SQL, Hadoop platforms to build Big Data products & platforms
• Experience with data pipeline and workflow management tools: NIFI, Airflow.
• Comfortable in developing shell scripts for automation
• Proficient in standard software development, such as version control, testing, and deployment
• Demonstrated basic knowledge of statistical analytical techniques, coding, and data engineering
• Curiosity, creativity, and excitement for technology and innovation
• Demonstrated quantitative and problem-solving abilities
• Motivation, flexibility, self-direction, and desire to thrive on small project teams
• Good communication skills - both verbal and written – and strong relationship, collaboration skills, and organizational skills
• At least a Bachelors degree in Computer Architecture, Computer Science, Electrical Engineering or equivalent experience. Postgraduate degree is an advantage
The following skills will be considered as a plus
• Experience with visualization tools like tableau, looker
• Hands-on experience with cloud computing and big data frameworks e.g. GCP, AWS, Azure, Flink, Elasticsearch, and Beam
• Knowledge in MLOps frameworks such as TensorFlow Extended, Kubeflow, or MLFlow
• Experience participating in complex engineering projects in an Agile setting e.g. Scrum
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