22/11 Pankhuri Jain
HR at Moodys

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Moodys - Lead Full Stack Machine Learning Architect - Deep Learning/Artificial Intelligence (10-15 yrs)

Anywhere in India/Multiple Locations Job Code: 383184

Job Title : Lead Full-Stack Machine Learning Architect

Entity : MA

Line Of Business/Department : Emerging Businesses Unit

Location : India

Job Code : Tbd

Reporting To : Senior Director, Ml And Ai - Emerging Business Unit

The Role / Responsibilities :

- The Lead Full-Stack Machine Learning Architect is a core member of the Emerging Business Unit (EBU) team, reporting to the Senior Director, ML and AI, Emerging Business Unit.

- This is a newly formed, highly visible team that is key to Moody's Analytics (MA) long-term growth strategy that will lead our efforts to better understand and adapt to an environment characterized by widespread, technology-driven change.

- The EBU is charged with supporting innovation within our existing LOBs, developing opportunities in the - whitespace-, enhancing our innovation process and understanding customers- technology preferences.

- The Lead Full-Stack Machine Learning Architect will, under the guidance of the Senior Director ML and AI, design, develop, and implement innovative Data Science and Data Engineering, Machine Learning, AI, deep learning, NLP, solutions that will advance Moodys Analytics capabilities across multiple business lines .

- This position will also lead and co-mentor data scientists and data engineers in the EBU AI-ML functions at India, provide day-to-day direction, oversight, and management of the local team, and report directly to the Senior Director, ML and AI, EBU in the USA.

The role will, under guidance of Senior Director ML and AI, ensure that the India teams short-term objectives and milestones, and longer term strategic goals are met, and communicate progress regularly to leadership in the US. The candidate tasks and responsibilities will include the following :

- Architect, develop, lead, and integrate emerging Data Science and Data Engineering/ML/AI/NLP / solutions and be conversant with latest developments across the entire technology stack

- Identify, architect, develop and scale new end-to-end solutions in ML/AI/NLP/Data Science and Data Engineering, working closely with the ML team at MA headquarters to help advance automation, knowledge discovery, decision-making and insights, and streamline business processes or enable new capabilities

- Architect, develop (hands-on), scale and evaluate full-stack, end-to-end data-driven engineering solutions for innovative data-driven tools

- Mentor, guide daily tasks and functions of local team of data scientists, data engineers, and as needed, architect, design and develop solutions for data science, data engineering (including data-ingest, data-wrangling, algorithm integration, algorithm improvement, and visualization) and evaluation.

- Integrate and scale novel data science solutions, and integrate with existing products or develop new products providing data-driven insights.

- Evaluate custom solutions through prototyping, POCs and quantitative metrics

- Use software management and development best practices, such as Agile, Scrum, Kanban, Waterfall, and employing tools for software development, management and documentation

- Discuss, brainstorm new advanced technology solutions with team members

- Explain complex architecture and data science processes to team members and managers

- Determine tradeoffs between internal technical implementation vs. leveraging existing solutions for new technology-based solutions and capabilities

- Prepare reports, presentations, for internal and external stakeholders.

Qualifications :

- Basic or advanced degree (BS / MS / PhD) with more than 10 years work experience.

- Education in a quantitative field such as CS, EE, Information sciences, Statistics, Mathematics, Economics, Operations Research, or related is preferred.

- At least 10 years work experience, with 5+ years as a full-stack engineer/architect, senior software or systems architect, data architect or principal Machine Learning engineering lead.

- Minimum 5 years experience in developing end-to-end full-stack data science, data engineering solutions and/or products applied to AI/ML/ NLP / deep learning / data-driven statistical analysis & modelling solutions in one or more domains

- Experience leading data science and data engineering teams and working in a global team environment spanning several countries

- Expert in applications of data science, data engineering and data-driven architectures and tools including data pre-processing, data warehousing, big data architectures and frameworks, scalable analytics, and visualization.

- Expert in the entire technology stack (infrastructure, middleware, software, UI and visualization, REST APIs) as applied to data-driven engineering solutions.

- Experience in data engineering, data management, data analytics middleware, platforms and infrastructure.

- Experience with developing custom solutions using REST, SOA frameworks

- Experience in cloud computing (AWS, Azure), virtualization, containers is a plus

- Well-rounded knowledge and experience with applied machine learning, AI, deep learning, data science, NLP, text analytics, unstructured data analytics, supervised/unsupervised learning in one or more domains.

- Strong, proven programming skills in Python, C/C++, Java, R, Matlab, Scala, and with machine learning and deep learning and Big data frameworks including TensorFlow, Keras, Caffe, Spark, Hadoop, NLP frameworks such as NLTK, SpaCY, Stanford NLP, and others.

- Experience with writing complex programs and implementing custom algorithms in these and other environments.

- Experience beyond using open source tools as-is, and writing custom code on top of, or in addition to, existing open source frameworks.

- Proven capability in demonstrating successful end-to-end advanced technology solutions (either prototypes, POCs, and/or products) using Data Science, Data Engineering, ML/AI/NLP/data science in one or more domains,

- Experience with software management and development best practices, such as Agile, Scrum, Kanban, Waterfall, and tools and processes for software development and tracking

- Additional experience with GPU programming for training deep learning models, and cloud environments such as AWS, Azure is a plus

- Excellent communication skills (oral and written) and ability to work in a diverse team

- Experience in an applied advanced technology environment, working in an agile, innovation-lab culture to bring cutting-edge technologies to fruition, from initial concept to implementation

Working at Moodys :

- Moody's is an essential component of the global capital markets, providing credit ratings, research, tools and analysis that contribute to transparent and integrated financial markets. Moody's Corporation (NYSE:MCO) is the parent company of Moody's Investors Service, which provides credit ratings and research covering debt instruments and securities, and Moody's Analytics, which offers leading-edge software, advisory services and research for credit and economic analysis and financial risk management.

- The Corporation, which reported revenue of $3.0 billion in 2013, employs approximately 8,400 people worldwide and maintains a presence in 31 countries. Further information is available at www.moodys.com

- EEO Language Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or any other characteristic protected by law.

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