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Data Science Assistant Jobs in Dallas, TX (NOW HIRING)

Vytwo

Data Scientist - INDIA

Prosper, TX · On-site

Data Science - Structured Data / Text Data (NLP & GenAI) About the Role We are seeking a highly ... Ability to write clean, optimized code and leverage AI code assistants. ✅ NLP / GenAI Specific ...

Judge Group, Inc.

Data Scientist - IV

Dallas, TX · On-site

Independently work on data science projects and deliver innovative technical solutions to solve ... Assist engagement with key business stakeholders in discussion on business strategies and ...

Toyota

Data Scientist

Plano, TX · On-site

You should not apply for this role if you will require Toyota to assist with immigration support or ... This role is ideal for someone who will thrive working at the intersection of computational science ...

Toyota

Data Scientist

Plano, TX · On-site

You should not apply for this role if you will require Toyota to assist with immigration support or ... PHD in a quantitative or technical discipline (CS, Engineering, Data Science, Statistics ...

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Data Science Assistant information

What is a data science assistant?

Data Science Assistants are professionals who support data scientists and analytics teams by handling tasks such as data collection, data cleaning, preparing datasets, conducting preliminary analyses, and creating visualizations. They often work with large datasets, assist in maintaining data integrity, and help automate routine processes. Their role allows data scientists to focus on more complex modeling and analytical work, making the overall workflow more efficient. Data Science Assistants typically have a foundational understanding of statistics, programming (such as Python or R), and data management tools.

What are the key skills and qualifications needed to thrive as a data science assistant?

To thrive as a Data Science Assistant, you need a solid understanding of statistics, data analysis, and programming (often with a background in mathematics, computer science, or a related field). Familiarity with tools like Python or R, data visualization software, and experience with databases or spreadsheet systems are typically required. Attention to detail, strong problem-solving abilities, and effective communication set outstanding candidates apart. These skills are crucial for supporting data-driven decision-making and ensuring accurate, actionable insights for organizations.

How does a data science assistant typically collaborate with data scientists and other team members on projects?

As a Data Science Assistant, you will frequently support data scientists by preparing datasets, conducting preliminary data analysis, and creating visualizations. You will often work closely with analysts, engineers, and subject matter experts to gather requirements and ensure data is cleaned and formatted appropriately. Collaboration is a key part of the role, as you may participate in team meetings, share findings, and help with documentation to keep projects running smoothly. This supportive environment provides an excellent opportunity to learn from experienced professionals and gain exposure to the full data science workflow.

What is the difference between Data Science Assistant vs Data Analyst?

AspectData Science AssistantData Analyst
Required CredentialsBachelor's in Data Science, Statistics, or related fieldBachelor's in Statistics, Mathematics, or related field
Work EnvironmentTech companies, research labs, data-driven departmentsBusiness, finance, marketing, healthcare sectors
Employer & Industry UsageUsed in data science teams for supporting models and analysisUsed across industries for interpreting data and generating reports

While both roles involve working with data, a Data Science Assistant typically supports data science projects, focusing on data preparation and model testing. A Data Analyst primarily interprets data to generate insights and reports. The roles overlap in skills and work environments but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Data Science jobs in Dallas, TX?

The most popular types of Data Science jobs in Dallas, TX are:

What are popular job titles related to Data Science Assistant jobs in Dallas, TX?

For Data Science Assistant jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Data Science Assistant jobs in Dallas, TX look for?

The top searched job categories for Data Science Assistant jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Data Science Assistant jobs?

Cities near Dallas, TX with the most Data Science Assistant job openings:

Data Science Assistant jobs near you
Infographic showing various Data Science Assistant job openings in Dallas, TX as of August 2026, with employment types broken down into 5% Internship, 81% Full Time, 9% Part Time, 2% Temporary, and 3% Contract. Highlights an 93% In-person, and 7% Remote job distribution.

Data Scientist - INDIA

Prosper, TX • On-site

Vytwo
See more jobs at Vytwoexternal

Full-time

Re-posted 16 days ago

Job description

Role: Data Scientist - INDIA
Location: Hyderabad / Noida, INDIA
*Consultants local to INDIA are eligible.Category: Data Science – Structured Data / Text Data (NLP & GenAI)
About the Role

We are seeking a highly skilled Data Scientist (3–7 years of experience) to join our team and work across two major data science domains:
  1. Structured Data (80–90%) – Predictive analytics, forecasting, cost estimation, likelihood modeling, and batch‑oriented machine learning pipelines.
  2. Text / Unstructured Data (NLP & GenAI) – Building low‑latency real‑time systems using deep learning, LLMs, prompt engineering, and agentic AI frameworks.
This role requires strong expertise in Big Data processing, modern ML tools, and the ability to build scalable, production-ready data science solutions.
Key Responsibilities

Structured Data – Machine Learning & Analytics

  • Build, deploy, and optimize ML models for predictive analytics, forecasting, classification, and regression.
  • Perform large-scale feature engineering using PySpark and Big Data tools.
  • Work on batch pipelines, model versioning, and experiment tracking.
  • Develop cost estimation and risk/likelihood models using statistical and ML techniques.
Text Data / NLP / GenAI

  • Build NLP pipelines using deep learning frameworks such as PyTorch, TensorFlow, or similar.
  • Develop real‑time, low‑latency inference systems for text classification, embeddings, semantic search, summarization, and retrieval.
  • Create prompts, context graphs, and agentic workflows for LLM-based systems.
  • Apply knowledge of prompt engineering, context engineering, and autonomous agent frameworks to production systems.
Core Data Science Engineering & MLOps

  • Work in Databricks for ETL, feature engineering, ML training, and orchestration.
  • Use Azure services for model deployment, data pipelines, and infrastructure.
  • Collaborate using Git-based workflows; leverage tools like GitHub Copilot, Claude Code, etc.
  • Implement model monitoring, observability, drift detection, and performance tracking.
Required Skills & Experience

✅ Core Skills

  • Strong hands-on experience with Databricks (Delta Lake, MLflow, Job Orchestration).
  • Excellent PySpark skills for large-scale distributed data processing.
  • Proficiency in Azure cloud services (ADF, Azure ML, AKS, Databricks on Azure).
  • Strong understanding of ML algorithms, statistical methods, and data analysis.
  • Experience with deep learning frameworks:
    • PyTorch
    • TensorFlow
    • Transformers (HuggingFace)
  • Experience with model monitoring and ML observability.
  • Ability to write clean, optimized code and leverage AI code assistants.
✅ NLP / GenAI Specific Skills

  • Prompt engineering (task prompts, chain of thought, tool calling, retrieval prompts).
  • Context engineering (retrieval pipelines, RAG, memory management, context structuring).
  • Knowledge of LLM-based agentic frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.).
  • Experience with vector databases and embedding models is a plus.
Good to Have Skills

  • Experience with containerization (Docker, Kubernetes, AKS).
  • Experience deploying models to production (REST APIs, real-time endpoints).
  • Knowledge of streaming technologies (Kafka, EventHub, Spark Streaming).
  • Understanding of CI/CD for ML (Azure DevOps / GitHub Actions).
Who You Are

  • A problem solver who is comfortable working with both structured and unstructured data.
  • Someone who enjoys using modern AI tools to accelerate development.
  • A data scientist who writes clean, production-grade code.
  • A collaborator who thrives in cross-functional teams and fast-paced environments.

Flexible work from home options available.