Sr Data Scientist Engineer Job at Rapinno Tech in Irving

About the job Sr Data Scientist Engineer

VERY URGENT AND IMMEDIATE NEED.

Note: Need Only US Citizen, Green Card, EAD-GC, J2 EAD, H4 EAD, L2 EAD, and TN Visa.

Job Title: Sr Data Scientist Engineer
Location: Irving(TX) , Alpharetta(GA), Basking Ridge (NJ), Irvine (CA) Hybrid Note: Need Only Local
Duration: Long Term Contract

Need Telecom Background working Experience

Required Skills:

Data Science

AI

Big Data/ Hadoop

Python

Cloud- AWS/GCP

Job Description:

Need minimum 08+ years of experience

What were looking for... You are an accomplished Data Scientist, a recognized Machine Learning expert, and a thought leader in AI Technology and business innovation.

You are a master at analyzing big data.

Required: Formal education: Bachelors degree with six or more years of relevant work experience as a Data Scientist practicing model development for business applications; Or a Master's Degree in Computer Science, Statistics, Math, Economics, Engineering, or Data Science related fields with four or more years of relevant experience as a data scientist or machine learning engineer.

Hands‑on experience in building machine learning and statistical models using Python, PySpark, Machine Learning libraries, SQL.

Experience in computing/programming skills; proficiency in Python, R, and Linux shell script.

Experience in data management and data analysis in a relational database, Hadoop and Spark.

Experience with Cloud computing platform such as GCP or AWS Strong communication and interpersonal influencing skills.

Excellent problem solving and critical thinking capabilities.

Desired: A Ph.D. in Computer Science, Statistics, Math, Economics, Engineering, or Data Science, with two or more years of experience in practicing machine learning and data science in business.

Expertise in deep learning, NLP, reinforcement learning, recommender system, etc.

Experience in leading large scale data science projects and delivering from end to end.

Experience with building data pipelines, model framework and model deployment.