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Associate Data Scientist Deep Learning Jobs in Texas

Role Overview We are seeking a Data Scientist to help build the next generation of industrial ... Time-series forecasting, Deep learning, Statistical modeling, Unsupervised learning, Physics ...

New

... and data science solutions. The ideal candidate will have expertise in predictive modeling, deep learning, NLP, and large-scale data analytics, with hands-on experience building end-to-end ML ...

Cymertek Corporation is seeking a curious and innovative Data Scientist to join their team and help ... Citizenship) Preferred : • Knowledge of deep learning frameworks • Familiarity with cloud ...

New

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... Demonstrated experience using machine learning, deep learning, statistical methodology, and ...

As a Data Scientist/Data Science Specialist for Adidev Technologies Inc., you will be enhancing and ... Demonstrated experience using machine learning, deep learning, statistical methodology, and ...

The Senior Data Scientist will focus on building scalable AI/ML models and services, partnering ... machine learning, deep learning and generative AI models. • Use software engineering best ...

Principal Associate, Data Science

Plano, TX · On-site

$56K - $56K/yr

Plano 5 (31065), United States of America, Plano, Texas Principal Associate, Data Science Principal ... Build machine learning models through all phases of development, from design through training ...

Principal Associate, Data Science

Plano, TX · On-site +1

$56K - $56K/yr

Plano 5 (31065), United States of America, Plano, Texas Principal Associate, Data Science Principal ... Build machine learning models through all phases of development, from design through training ...

... deep learning solutions. * DevOps & MLOps: Proficient in CI/CD pipelines, containerization (Docker, Kubernetes), and cloud platforms (Databricks, AWS, GCP, Azure). Experienced with infrastructure-as ...

Deep understanding of Lean product principles, software development lifecycle, and machine learning ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

Deep understanding of Lean product principles, software development lifecycle, and machine learning ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

Deep understanding of Lean product principles, software development lifecycle, and machine learning ... That's why we hire associates with the intellectual curiosity, energy and drive to want to make a ...

... deep learning frameworks (e.g., pytorch, tensorflow, huggingface), LLM frameworks (e.g., LangChain, LlamaIndex), SQL/relational databases (e.g., Oracle), NoSQL databases (e.g., MongoDB, graph ...

... Learning NLP Models and good familiarity with Gen AI Models. REQUIRED SKILLS * 7+ years of ... Deep understanding and some exposure to new Gen AI Open-source Models * At least 5 years ...

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Associate Data Scientist Deep Learning information

What is the difference between Associate Data Scientist Deep Learning vs Data Scientist?

AspectAssociate Data Scientist Deep LearningData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related; familiarity with deep learning frameworksBachelor's or Master's in CS, Statistics, or related; broader data analysis skills
Work EnvironmentFocus on developing deep learning models, often in AI or ML teamsBroader data analysis, visualization, and modeling across various projects
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, retail, tech, and more

The main difference is that Associate Data Scientist Deep Learning specializes in developing deep learning models, requiring specific knowledge of neural networks and frameworks. Data Scientists have a broader scope, including traditional data analysis, statistical modeling, and visualization. Both roles often require similar educational backgrounds but differ in technical focus and project types.

What are the most commonly searched types of Data Scientist Deep Learning jobs in Texas? The most popular types of Data Scientist Deep Learning jobs in Texas are:
What cities in Texas are hiring for Associate Data Scientist Deep Learning jobs? Cities in Texas with the most Associate Data Scientist Deep Learning job openings:

Full-time

Posted 4 days ago

New


Job description

Role Overview

We are seeking a Data Scientist to help build the next generation of industrial intelligence for our operations, reliability, maintenance, and performance optimization. This role sits at the intersection of applied machine learning, large-scale industrial telemetry, physics-informed analytics, and cloud software platforms.

You will develop and productionize advanced AI/ML models that transform high-frequency operational turbine data into actionable customer intelligence — reducing forced outages, improving availability, lowering O&M costs, and enabling predictive operations across fleets of industrial assets.

Key Responsibilities

Machine Learning

  • Design, develop, and deploy machine learning models for:
  • Predictive maintenance, Anomaly detection, Failure prediction, Remaining useful life (RUL) estimation, Operational optimization, Fleet-wide analytics
  • Build and train models using large-scale industrial telemetry and operational datasets.
  • Apply advanced ML techniques including:
  • Time-series forecasting, Deep learning, Statistical modeling, Unsupervised learning, Physics-informed ML approaches
  • Develop algorithms capable of handling noisy, sparse, and real-world operational data.
  • Evaluate model performance using operational KPIs and real-world production feedback.

Production ML & MLOps

  • Build scalable production pipelines to operationalize ML models into customer-facing products.
  • Develop infrastructure for:
  • Feature engineering, Automated retraining, Model monitoring, Drift detection, Experiment tracking, CI/CD for ML workflows
  • Deploy models across cloud and edge-computing environments.
  • Collaborate closely with software engineering teams to integrate ML capabilities into SaaS applications and operational workflows.

Cross-Functional Collaboration

  • Partner with controls engineers, reliability engineers, product managers, and software teams to solve complex industrial problems.
  • Translate operational challenges into scalable data science solutions.
  • Communicate technical findings and recommendations to both technical and non-technical stakeholders.
  • Contribute to technical strategy and mentor junior engineers and data scientists.

Required Qualifications

  • Bachelor’s in Computer Science, Data Science, Statistics, Engineering, Physics, Applied Mathematics, or related quantitative field.
  • 3+ years of experience in machine learning, applied AI, or production data science systems.
  • Strong proficiency in:
  • Python, SQL, Scientific computing and data engineering workflows
  • Experience with modern ML frameworks and tools such as:
  • PyTorch, TensorFlow, Scikit-learn, XGBoost, Spark
  • Experience building and deploying production ML systems in cloud environments (AWS, Azure, or GCP).
  • Strong understanding of:
  • Time-series analytics, Statistical inference, Feature engineering, Distributed systems, Production software engineering practices
  • Experience with containerization and orchestration tools such as Docker and Kubernetes is a plus.

Preferred Qualifications

  • Experience in industrial systems, IIoT, energy, power generation, aerospace, or reliability engineering.
  • Familiarity with:
  • Data Streaming platforms (Azure/AWS/GCP services), MLflow, Real-time analytics systems
  • Experience deploying ML systems in operationally critical or high-availability environments.
  • Knowledge of digital twins, edge AI, or physics-informed machine learning techniques.