Senior Data Scientist, Irving Tx

Job Title: Senior Data Scientist

Location: Irving, TX -Hybrid (2-3 Days onsite)

Exp: 12+Years

Duration: Long Term

Required Qualifications:

• Good experience deploying models in Production.
• Another with PyTorch/Torch Lighting knowledge to help us build/edit models.
• Ex-Telecom Projects Plus
• Deploying experience is must
• Work with a focus on MLOps

Here is the Detailed job description

Data Scientist:

• Independently create and/or Assist lead Data Scientists in developing various kinds of machine learning models for personalized customer service domain using state of the art ML algorithms such as GBM, XGBoost, Deep Learning etc. on CPU and GPU environments
• Conduct pre-modeling activities such as data clean up, exploratory data analysis, scaling/normalization, feature engineering, etc. with data in Google Cloud Platform ecosystem, notebooks
• Proficient with standard Data Science Libraries such as NumPy, Pandas and Deep learning. In addition, proficiency in libraries for GPUs is a huge plus
• Knowledge of Pytorch or Tensorflow and experience with modern neural NLP approaches is a plus.
• Developing test cases and executing test cases for developed ML models
• Assist in performance/load testing/monitoring of the deployed models
• Documenting the models, features and any decisions made during modeling
• Assist ML engineers during solution deployment on on-prem and AWS for authoring/making changes to API wrappers
• Ability to rapidly learn the current state of the project and independently work with minimal assistance after the initial ramp up time

ML Engineer:

• Bachelor's degree.
• Four or more years of work experience in software development/ML Engineering jobs.
• At least two years of experience are in ML Engineering areas.
• Experience with Python/Java programming
• Experience in cloud based development and production environments - AWS, GCP and On-prem clusters
• Familiarity with large scale cloud-based platform/pipeline development and productization.
• Have experience with basic ML practices and standard workflows.

Even better if you have one or more of the following:

• Understand basic data science concepts and common needs from Data Scientists.
• Strong collaboration skills and communication skills, especially when involving (non-tech) business stakeholders.
• Experience with cloud infrastructures/cloud Ops
• Familiar with CI/CD process and common frameworks.
• Familiar with MLOps/DevOps.