Data Scientist and Analytics Engineer

SherlockTalent; New York (NY); Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

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Job summary

A leading technology firm is seeking a Data Scientist and Analytics Engineer for a fully remote role. The successful candidate will collaborate closely with HPC engineers, utilize various statistical programming languages and ML frameworks, and contribute to the development of innovative machine learning applications. Candidates with experience in cloud deployment and a strong desire to learn new technologies will be preferred.

Qualifications

• 1+ years experience working with Python and SQL.
• Familiar with machine learning and deep learning frameworks.
• Knowledge of visualization libraries like bokeh or holoviews.

Responsibilities

• Develop machine learning applications in collaboration with client teams.
• Run experiments and tests to improve ML model performance.
• Create tools for monitoring and analyzing model accuracy.

Skills

Python

SQL

Machine Learning

Data Visualization

Tools

TensorFlow

PyTorch

scikit-learn

Docker

Job description

Job Title:Data Scientistand Analytics EngineerLocation:100% REMOTEJob Type:Perm Full-TimeSalary:$120K – $170K Depending on ExperienceJob:7170

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 usesLinux 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 forHPC simulations
• The candidate will also assist in Research & Developmentfor our next generation machine learning products in Network Simulations
• The candidate is expected to have experience working with data pipelines and ML frameworks.

Minimal requirements

• 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

Responsibilities include (not limited to):

• 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

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