Data Scientist and Analytics Engineer

Our client runs a High-Performance Computing Platform (HPC) on AWS along with a multitude of opensource technologies and middleware. The systems run in the Cloud so we always think cloud first! Our team uses Linux and some Windows. We are removing barriers that keep the product team from executing faster than our competitors and releasing a clean, quality product. This means supporting & testing our stack in a public cloud as well as with distributed schedulers, logging solutions, metrics, storage archiving, and optimization of HPC application cost & performance. About the Job

• The candidate will work closely with HPC engineers to build reusable components for generating real-time insights and analytics for HPC simulations
• The candidate will also assist in Research & Development for our next generation machine learning products in Network Simulations
• The candidate is expected to have experience working with data pipelines and ML frameworks., * Working with internal teams and clients to develop machine learning applications
• Run machine learning tests and experiments
• Extend existing ML libraries and frameworks when necessary
• Study and transform data science prototypes
• Develop processes and tools to monitor and analyze model performance and data accuracy
• Develop an A/B testing framework and test model quality

Preference will be given to candidates with the following:

• A drive to learn and master new technologies and techniques
• Familiar with development and deployment on Cloud environment (AWSCLI, Boto3, Docker and etc)
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark and etc
• Experience with CUDF and other CUDA-based libraries, SherlockTalent is committed to protecting and respecting your privacy. We’ll only store and use your personal information to administer your account and to provide you with information by email and SMS related to your account, job search, and career. Referral Source Submit Copyright © 2026 SherlockTalent | Designed by Josh Piller | Maintained by We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies. . Manage consent Close Privacy Overview This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt out of these cookies. But opting out of some of these cookies may affect your browsing experience. Necessary Always Enabled Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensure the basic functionalities and security features of the website. These cookies do not store any personal information. Non-necessary Any cookies that may not be particularly necessary for the website to function and are explicitly used to collect user personal data via analytics, ads, and other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

• Experience using statistical computer languages (Python, Golang, SQL, etc.) to manipulate data and draw insights from large data sets

• 1+ years working with Python programming
• 1+ year working with SQL (Postgresql)

• Knowledge and experience in machine learning algorithms:

• Random Forest, boosting, decision trees, clustering
• LSTM, Reinforcement learning
• 1+ years working with scikit-learn, or related machine learning framework
• 1+ years working with Tensorflow, Pytorch, or related deep learning framework
• 1+ years working with bokeh, holoviews, or related visualization library
• 1+ years working with a RDBMS

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