Morgan Stanley Pvt Ltd

Machine Learning Engineer (BB-68697)

Found in: Talent IN

Morgan Stanley is a leading global financial services firm providing a wide range of investment banking, securities, investment management and wealth management services. We advise, originate, trade, manage and distribute capital for governments, institutions and individuals. As a market leader, the talent and passion of our people is critical to our success. Together, we share a common set of values rooted in integrity, excellence and strong team ethic. We provide you a superior foundation for building a professional career where you can learn, achieve and grow. Technology/Role/Department at Morgan Stanley Technology is the key differentiator that ensures that we manage our global businesses and serve clients on a market leading platform that is resilient, safe, efficient, smart, fast and flexible. Technology redefines how we do business in global, complex and dynamic financial markets. We have a large number of award winning technology platforms that help to propel our Firms businesses to be the top in the market. Our India technology teams are based in Mumbai and Bengaluru. We have built strong techno-functional teams which partner with our offices globally taking global ownership of systems and products. We have a vibrant and diverse mix of technologists working on different technologies and functional domains. There is a large focus on innovation, inclusion, giving back to the community and sharing knowledge. Wealth Management Technology (WMIMT) is responsible for the design, development, delivery, and support of the technical platform behind the products and services used by the Business. Morgan Stanley Wealth Management (WM) is a product of the acquisition of Smith Barney from Citigroup, which was completed in June 13. Its core client base is individual investors, small- to medium-size businesses and institutions, and high net worth families and individuals. In the second half of 14, WM reached a milestone, with its business having surpassed $2 trillion in total client assets. We are seeking a Senior Machine Learning Engineer with expertise in architecture, design and development of data and ML centric applications at scale. The right candidate should have a background in data engineering and requisite experience working with Machine learning (ML) algorithms and Frameworks. The role is a confluence of engineering (programming), ML and data analysis. Knowledge of Data Science is a plus. This position is for the Risk Analytics team which is part of Artificial Intelligence and Knowledge Management group within Morgan Stanley Wealth Management. The team is comprised of members located in NY-United States, Mumbai-India and Bengaluru-India. The team partners with various businesses and IT groups within firm to develop analytics and ML powered solutions aimed at Portfolio risk assessment, business activity monitoring and high volume application activity log analytics. The team accumulates data from a variety of internal and external upstream systems in order to develop statistics, models, dashboards and metrics for the Technology Risk team. The right candidate has (Responsibilities) Design machine learning systems, and oversee the platform on which the solutions would be deployed. Create ML model training, validation and hyper-parameter search pipelines Design and Build distributed, scalable, and reliable data pipelines that ingest and process data at scale and in real-time Ensure data integrity through Data quality, validation, Governance and Transparency Explore new data sources and data. Select appropriate datasets and their representation methods. Perform data analysis (statistical and otherwise), to derive inferences from data Production deployment and Model monitoring to ensure stable performance and adherence to standards Evaluate state-of-art data-centric technologies and prototype solutions to improve our architecture and platform Work with business teams to understand requirements and develop relevant solutions. Create presentations / visualizations for the leadership and business that would be able to explain complex outcomes and emphasize business impact. Lead data science and engineering team in a distributed agile framework Qualifications Primary skills Experienced professional with 7-10 years of experience developing and implementing ML models in Big data ecosystem i.e. Hadoop, Spark, Kafka, HBase, Hive / Impala, Cassandra, MongoDB or any other similar distributed computing technology Proficiency in applied Machine learning and statistical modeling techniques in Python / Java / Scala. Experience using ML platforms such as Dataiku / Databricks is a plus. Expertise in at least one Programming language Python / Java / Scala Proficiency in data analysis using complex and optimized SQL and / or above mentioned technologies Understanding of data structures, data modeling and software architecture Experience in architecture, design and implementation of data intensive applications for practical use-cases Expertise in visualizing large datasets and developing articulate dashboards in an efficient manner People and stakeholder management experience and excellent organizational skills and follow-through Ability to work in fast paced, dynamic and geographically distributed environment Good written and verbal communication skills Good to have skills In-depth understanding of Machine Learning and Statistics, in addition to above Experience in domains Financial Risk and Log Analytics Worked on large scale Anomaly Detection use cases Practical knowledge of Natural Language Processing (NLP) and/or Neural network implementation Tableau for data visualization Experience working in an Agile environment

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