We are:
The Machine Learning team in the Wealth Management (WM) Analytics & Data (A&D) organization at Morgan Stanley is dedicated to delivering machine learning solutions to a wide range of internal stakeholders in wealth management. Our team specializes in a variety of applied research areas, including recommender systems, client personalization, marketing propensity models, and asset and client attrition models. We provide machine learning solutions to a diverse group of internal stakeholders, delivering delightful new experiences to over 15 million WM clients.
Responsibilities:
- Design and develop robust machine learning solutions that drive real business results.
- Work with cross-functional teams to integrate ML solutions into business decision-making processes.
- In collaboration with the MLOps team deploy the Machine Learning models in production environment and monitor their performance.
- Dive into massive datasets to uncover trends, patterns and insights that inform business strategy and drive growth.
- Experiment with the advanced techniques to drive innovation and improve model performance.
- Participate in code reviews to ensure our code is top-notch and always improving.
- Mentor and guide junior team members to help them develop their skills and expertise.
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Requirements:
Technical skills:
- 5 years of work experience in an analytical field, of which at least 2 years was spent in a Data Science position.
- Proven experience of leading and implementing 2+ end-to-end Data Science projects that have delivered business value and demonstrated financial impact.
- Comprehensive understanding of Machine Learning pipeline development and core algorithms in classification, regression, segmentation, ranking.
- Python, SQL proficiency.
- Experience with one of cloud computing platforms such as Databrics, AWS, GCP.
- Hands on experience with version control systems GitHub.
- Familiarity with MLFlow experiment tracking.
- Nice to have an experience with recommender systems, time series forecasting, neural networks, graph models, PySpark.
Educational Background:
- Master's degree in computer science, Engineering, or related quantitative field.
- PhD as a plus.
Professional skills:
- Strong communication skills and proficiency in English.
- Project leadership capabilities.
WHAT YOU CAN EXPECT FROM MORGAN STANLEY:
We are committed to maintaining the first-class service and high standard of excellence that have defined Morgan Stanley for over 85 years. At our foundation are five core values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - that guide our more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find trusted colleagues, committed mentors and a culture that values diverse perspectives, individual intellect and cross-collaboration. We Firm is differentiated by the caliber of our diverse team. While our company culture and commitment to inclusion define our legacy and shape our future, helping to strengthen our business and bring value to clients around the world. Learn more about how we put this commitment to action: morganstanley.com/diversity. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry.
We're committed to bringing passion and customer focus to the business.
Certified Persons Regulatory Requirements:
If this role is deemed a Certified role and may require the role holder to hold mandatory regulatory qualifications or the minimum qualifications to meet internal company benchmarks.
Flexible work statement
Interested in flexible working opportunities? Morgan Stanley empowers employees to have greater freedom of choice through flexible working arrangements. Speak to our recruitment team to find out more.
Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential. Our skilled and creative workforce is comprised of individuals drawn from a broad cross section of the global communities in which we operate and who reflect a variety of backgrounds, talents, perspectives, and experiences. Our strong commitment to a culture of inclusion is evident through our constant focus on recruiting, developing, and advancing individuals based on their skills and talents.