MORE ABOUT THIS JOB Consumer and Investment Management (CIMD) The Consumer and Investment Management Division includes Goldman Sachs Asset Management (GSAM), Private Wealth Management (PWM) and our Consumer business (Marcus by Goldman Sachs). We provide asset management, wealth management and banking expertise to consumers and institutions around the world. CIMD partners with various teams across the firm to help individuals and institutions navigate changing markets and take control of their financial lives.
Consumer Consumer, externally known as Marcus by Goldman Sachs, is comprised of the firm's digitally-led consumer businesses, which include our deposits and lending businesses, as well as our personal financial management app, Clarity Money. Consumer combines the strength and heritage of a 150-year-old financial institution with the agility and entrepreneurial spirit of a tech start-up. Through the use of machine learning and intuitive design, we provide customers with powerful tools that are grounded in value, transparency and simplicity to help them make smarter decisions about their money. Your Impact Clarity Money is a business recently acquired by Goldman Sachs that offers a revolutionary AI- and machine learning-based product for consumers to improve their financial health. Ushering in a new era of mobile personal finance management apps, Clarity Money uses artificial intelligence and data science to help consumers make smarter financial decisions and get the most from their money. The revolutionary features allow users to cancel bills, get a better credit card and create a savings account, all from within the app, and all at the push of a button.
The Clarity Money team is actively seeking a motivated Data Engineer with proven industry experience in machine learning, data engineering and building robust data pipelines. Strong computer science fundamentals are key to success in this role. The ideal candidate should be an individual contributor, a positive team player and willing to get things done.
RESPONSIBILITIES AND QUALIFICATIONS Required Qualifications:
5+ years of relevant industry experience.
Solid engineering and programming skills. Ability to write high performance production quality code with Python and/or Scala.
Experience building efficient large-scale data pipelines and data warehousing solutions.
Strong SQL and NoSQL skills.
Knowledge about Docker, CircleCI, Jenkins, testing, version control systems is required.
Proficiency in building data pipeline from scratch and deploying them on cloud environment (AWS or similar).
Proven experience in processing large sets of data in batch and real time fashion using Hadoop, MapR, Spark, Kafka, Kinesis etc.
Ability to engage with other teams to design the optimal data architecture for a new scale platform and infrastructure to support data and analytics-based product innovation.
Proficiency in probability, statistics, feature engineering and exploratory data analysis and extracting insights using Python, R or similar tools. Eager to get your hands dirty.
Experience with consumer products/services (including but not limited to: consumer lending, mobile banking applications, deposits etc.).
Experience with deploying, maintaining and iterating over large-scale machine learning systems to drive improvement of current products and the development of novel features and products within the company's vision.
Experience with data visualization libraries like seaborn, D3Js or tools like Tableau.
Self-starter and curious.
ABOUT GOLDMAN SACHS The Goldman Sachs Group, Inc. is a leading global investment banking, securities and investment management firm that provides a wide range of financial services to a substantial and diversified client base that includes corporations, financial institutions, governments and individuals. Founded in 1869, the firm is headquartered in New York and maintains offices in all major financial centers around the world.