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Data Scientist

  • Data Scientist job type Posted on: Oct 21, 2026
  • Data Scientist experience level Saransh Inc
  • Data Scientist employment type Austin, Texas
  • Data Scientist employment type Onsite
  • Data Scientist salary CTC

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Job Title :

Data Scientist

Job Type :

Contract

Job Location :

Austin Texas United States

Remote :

No

Jobcon Logo Job Description :

Position Title: Data Scientist
Location: Austin, TX (5 Days Onsite)
Duration: 6 Months Contract
Job Description:
8+ years of hands-on experience in Data Science and Data Engineering, with a proven track record of designing and deploying enterprise-scale analytical solutions.
Expert-level proficiency in Python, alongside deep knowledge of Architectural Patterns for distributed computing and large-scale data processing (a must-have requirement).
4+ years of dedicated experience in MLOps and Productionalization, focusing on the end-to-end lifecycle of machine learning models (CI/CD for ML).
Strong understanding of Data Architecture, and real-time streaming architectures (e.g., Kafka or Spark Streaming).
Experience with Cloud Infrastructure (AWS/Azure/GCP) and containerization (Docker/Kubernetes) to build scalable, resilient environment for model training and inference.
Excellent system design and analytical skills, with a focus on model governance, security, and scalability of AI solutions.
Superior communication and leadership skills, with the ability to align technical roadmaps with business strategy and explain architectural trade-offs to executive stakeholders.
Proven ability to lead cross-functional teams, define technical standards, and drive the adoption of innovative data technologies in a fast-paced environment.

Jobcon Logo Position Details

Posted:

Oct 21, 2026

Reference Number:

4974-2279

Employment:

CTC

City:

Austin

Job Origin:

CIEPAL_ORGANIC_FEED

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Position Title: Data Scientist
Location: Austin, TX (5 Days Onsite)
Duration: 6 Months Contract
Job Description:
8+ years of hands-on experience in Data Science and Data Engineering, with a proven track record of designing and deploying enterprise-scale analytical solutions.
Expert-level proficiency in Python, alongside deep knowledge of Architectural Patterns for distributed computing and large-scale data processing (a must-have requirement).
4+ years of dedicated experience in MLOps and Productionalization, focusing on the end-to-end lifecycle of machine learning models (CI/CD for ML).
Strong understanding of Data Architecture, and real-time streaming architectures (e.g., Kafka or Spark Streaming).
Experience with Cloud Infrastructure (AWS/Azure/GCP) and containerization (Docker/Kubernetes) to build scalable, resilient environment for model training and inference.
Excellent system design and analytical skills, with a focus on model governance, security, and scalability of AI solutions.
Superior communication and leadership skills, with the ability to align technical roadmaps with business strategy and explain architectural trade-offs to executive stakeholders.
Proven ability to lead cross-functional teams, define technical standards, and drive the adoption of innovative data technologies in a fast-paced environment.

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