Engineering-L2-NEW YORK-Associate-Data Analytics Engineering-L2-NEW YORK-Associate-Data Analytics …

Goldman Sachs
in New York City, NY, USA
Festanstellung, Vollzeit
Seien Sie der erste Bewerber
Goldman Sachs
in New York City, NY, USA
Festanstellung, Vollzeit
Seien Sie der erste Bewerber
Engineering-L2-NEW YORK-Associate-Data Analytics
Your Impact
Security Platform Engineering within Core Engineering is responsible for providing an opinionated, standardized set of tools and services to enable building of secure applications at the firm. The hiring team is responsible for measuring the macro security risk posture of Core Engineering, by unifying disparate sources of data across various inventories, engineering implementations, as well as data logs generated by these standardized tools and services.
Are you are a data scientist looking for a role where you can have broad-reaching positive impact and are enthusiastic about applying your analytics skillset to broad range of problems in security, authentication, and cloud?
How will you fulfill your potential?
  • Responsible for expanding the team's analytic capabilities by building advances statistical models, including machine learning algorithms
  • Responsible for all aspects of the data analytics lifecycle such as data ingestion, cleanup, model building, training, and evaluation
  • Responsible for summarization and concise presentation of quantified risk posture to management using open source visualization techniques, tools, and libraries
  • Responsible for working with various enterprise data sources and inventories for acquiring any enrichment data set that will help with the required risk modeling
  • Design, develop, test, and deliver complex analytics in a range of programming environments on large data sets

Basic Qualifications
  • Strong verbal and written communication skills in English
  • Ability to multi-task and effectively prioritize work
  • 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 understandable manner
  • Strong sense of ownership and driven to manage tasks to completion
  • 4-6 years of relevant work experience in projects involving big scale data analytics and machine learning
  • Proven knowledge of industry leading data analysis tools such as Python, R and SQL
  • Experience in industry standard notebook technologies
  • Knowledge of data analytics stack in cloud, preferably AWS
  • Experience in data visualization using open source libraries (such as dash / plotly / ggplot2 and etc.)

Preferred Qualifications
  • Bachelors in Computer Science, or any other Engineering Discipline or Mathematics.
  • Interest in Cyber-Security, or Information Security is preferred
  • Strong mathematical background (linear algebra, probability, and statistics)
  • Excellent oral, written, and presentation communication skills


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 .

We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://

© 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

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