Engineering- Data Science and Machine Learning- Senior Machine Learning Engineer

Key Skills

Java Programming, Python Programming, C++, SQL, TensorFlow

Job Description

The financial industry thrives on data driven decision making. You will be joining the team that builds and operates foundational platform, used by the rest of Goldman Sachs to apply data science and machine learning to the daily operations of the firm. We take the best components from open source and major cloud providers and adapt and expand them to accommodate unique needs of the firm. The resulting systems are not only part and parcel of the daily life of hundreds of Goldman Sachs data scientists, but also play critical role in the experience of thousands of Goldman Sachs clients.

OUR IMPACT

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 is at the critical center of our businesses. Our dynamic environment requires strategic thinking that is innovative and produces smart solutions. The Goldman Sachs Data Science and Machine Learning Platform team provides high impact solutions for our data scientists responsible for solving problems of significant business value across multiple divisions of the firm. We build scalable and resilient systems using predictive modeling, natural language processing, anomaly detection, time series forecasting, deep learning, and other techniques on high-volume and highvelocity data.

HOW YOU WILL FULFILL YOUR POTENTIAL

A true greenfield opportunity, you will join the team as we embark on creating new, scalable and resilient data science tools for a complex industry. You will collaborate with data scientists and business leaders to understand challenges facing the firm and its clients. Your design and development work will contribute to a world-class client experience and optimize business performance.

• Develop machine learning models and conduct, write up, and defend in-depth analyses on the effectiveness of these models including statistical significance testing, interactive visualizations using Jupyter notebooks, and detailed risk reports for model governance – such work entails knowledge of risk modeling systems and machine learning, including algorithms (e.g. gradient-boosted trees), optimization techniques (e.g. stochastic gradient descent), and statistical methods for assessing and tuning their performance (e.g. cross-validation).
• Work with complex machine learning frameworks (e.g. Tensorflow) and store, experiment on, and serve models trained with this framework in production.
• Write, understand, debug and review production code in at least one programming language (Python primarily) leveraging advanced knowledge in version control (e.g. Git), version control software (e.g. Github), modern continuous integration/continuous deployment (CI/CD) technology
• Utilize above referenced technologies to write highly performant and maintainable code, version control it for shared development with a team of developers, and deploy it to production
• Understand and utilize academic papers containing the state of the art in machine learning, including papers published in recent conferences.

SKILLS & EXPERIENCE 

BASIC QUALIFICATIONS

• 5+ years of experience in systems using machine learning and other artificial intelligence techniques
• Prior experience in training , testing and productizing machine learning models and work on the systems that support the model predictions and data gathering used for model training.
  - Proven record of working with latest machine learning technologies and integrating them in production services
  - Knowledge of natural language processing and data annotation tools and technologies
• Working knowledge of more than one programming language (Python, Java, C++ etc.)
• Experience building and operating distributed systems on the cloud
• Experience working closely with data scientists and appreciation for their unique workflow
• Excellent interpersonal, communication and presentation skills, both written and verbal
• Ability to stay commercially focused and to always push for quantifiable commercial impact
• Ability to collaborate effectively across global teams and communicate complex ideas in a simple manner