Consumer and Wealth Management (CWM)

Across Consumer and Wealth Management (CWM), Goldman Sachs helps empower clients and customers around the world to reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking, and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for consumers to better spend, borrow, invest, and save. Across CWM, our growth is driven by a relentless focus on our people, our clients, and leading-edge technology, data, and design.

Consumer (MARCUS BY GOLDMAN SACHS)

The firms Consumer business, Marcus by Goldman Sachs, combines the entrepreneurial spirit of a startup with more than 150 years of experience. Today, we serve millions of customers across multiple products including lending, deposits, financial tools, and our partnership with Apple on Apple Card. We use innovative design, data, engineering, and other core capabilities to provide customers with powerful tools and products that are grounded in value, transparency, and simplicity. As we build a leading digital consumer bank and expand into new products and partnerships, we are looking for leaders and individual contributors to join our team.

You will be part of the data science function for Marcus cards business and the Marcus App that caters to end to end customer life cycle. This would include but is not limited to transaction data processing and understanding, customer behavior analysis, customer segmentation, and marketing targeting.

Consumer and Wealth Management (CWM)

Across Consumer and Wealth Management (CWM), Goldman Sachs helps empower clients and customers around the world reach their financial goals. Our advisor-led wealth management businesses provide financial planning, investment management, banking and comprehensive advice to a wide range of clients, including ultra-high net worth and high net worth individuals, as well as family offices, foundations and endowments, and corporations and their employees. Our consumer business provides digital solutions for consumers to better spend, borrow, invest, and save. Across CWM, our growth is driven by a relentless focus on our people, our clients and leading-edge technology, data and design.

Consumer (MARCUS BY GOLDMAN SACHS)

The firms Consumer business, Marcus by Goldman Sachs, combines the entrepreneurial spirit of a startup with more than 150 years of experience. Today, we serve millions of customers across multiple products including lending, deposits, financial tools, and our partnership with Apple on Apple Card. We use innovative design, data, engineering and other core capabilities to provide customers with powerful tools and products that are grounded in value, transparency and simplicity. As we build a leading digital consumer bank and expand into new products and partnerships, we are looking for leaders and individual contributors to join our team.

RESPONSIBILITIES AND QUALIFICATIONS

Your Impact

You will be part of the data science function for Marcus that caters to end to end Customer life cycle. You will analyze noisy and unstructured data to bring insights to business to optimize decision making, and build and deploy ML models with colleague data scientists and engineers to improve efficiency of customer-agent engagements at scale. Those will save hours of customer and agent, and millions of dollars for business.

We have a fast paced result driven culture and we are looking for individuals who are proactive and can work with a sense of urgency. You should have a sense of ownership and should be able to drive results independently.

Job Summary and Responsibilities

1. Data mining using state-of-the-art methods
2. Process, clean, and verify the integrity of data used for analysis
3. Do ad-hoc analysis and presenting results in a clear manner to non-technical people
4. Select features, build and optimize models using machine learning techniques with noisy and unstructured, text data
5. Document model development and performances
6. Enhance business workflows by providing insightful analysis
7. Create automated process of identifying bad actors

QUALIFICATIONS

• Excellent understanding of machine learning techniques and algorithms, such as gradient boosting decision tree, k-NN, etc.
• Experience with common data science toolkits, such as Python (Pandas,, NumPy, Scikit-learn) and Spark
• Experience with AWS and technology stacks is plus
• have a strong problem-solving ability
• Excellent communication skills and a business mindset
• Experience with data visualization tools,
• Good applied statistics skills, such as distributions, statistical testing, regression, etc.
• Good scripting and programming skills
• a minimum of Bachelors degree in Mathematics, Computer Science, or Statistics, or in a relevant discipline

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. Were committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

The Goldman Sachs Group, Inc., 2021. All rights reserved.Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity