Job Information
Goldman Sachs & Company Engineering-L2-New York-Vice President-Software Engineering in New York, New York
What We Do
At Goldman Sachs, our Engineers don't just make things - we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.
Engineering Organization in Goldman Sachs includes the Technology and Strategist groups across various business functions. Our engineers are responsible for building and deploying innovative technical and quantitative solutions for our clients and our firm. As Foundational Infrastructure, we run the services that underpin the firm. We provide transparent management of infrastructure services and products onsite and in the cloud, with a focus on security, efficiency, and resilience. Our aim is to accelerate our Businesses and Engineers, whilst optimizing for end-to-end delivery appropriate to the firm's stack, scale, and investment.
Are you a data scientist looking for a role where you can have broad-reaching positive impact and enthusiastic about applying your analytics skillset to broad range of problems in engineering?
How will you fulfill your potential?
- Generate and present concise engineering and business insights to help organization make data driven decisions.
- Collaborate with subject matter experts across multiple pillars of engineering to derive requirements for analytics and metrics.
- Architect and build an end-to-end analytics platform that is scalable and reusable and will enable rapid development of analytics and metrics.
- Engage various stakeholders to locate, ingest and model siloed data sets that are essential for a comprehensive data analytics function.
- Expand the team's analytic capabilities by building advances statistical models, including predictive models.
- Drive all aspects of the data lifecycle including data ingestion, cleanup, modeling, training, and evaluation.
- Design, develop, test, and deliver complex analytics on large data sets and unstructured log data.
Basic Qualifications
- 5-10 years of relevant work experience in projects involving large scale data analytics and machine learning.
- Proven knowledge of industry standard data analytics languages such as Python, R and SQL.
- Practical data wrangling skills (SQL, Python, R).
- Experience in data visualization using industry standard tools (Tableau, Plotly, ggplot2, RShiny and etc.).
- Experience in data science notebook technologies (Jupyter, Zeppelin, RMarkdown).
- Knowledge of data analytics stack in cloud, preferably AWS.
- Highly motivated self-starter who can provide thought leadership in data science.
- Responsive to challenging tasks.
- Ability to document and explain technical details in a concise and impactful manner.
- Strong sense of ownership and driven to manage tasks to completion.
Preferred Qualifications
- Experience in Financial Services
- Experience in Cloud Analytics stack
- Bachelors in Computer Science, or any other Engineering Discipline or Mathematics.
- Excellent oral, written, and presentation communication skills.
The Goldman Sachs Group, Inc., 2018. All rights reserved Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Vet.
Minimum Salary: 31200.00 Maximum Salary: 31200.00 Salary Unit: Yearly