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Weekend Data Scientist Deep Learning Jobs (NOW HIRING)

Data Science Structured Data / Text Data (NLP & GenAI) About the Role We are seeking a highly ... Text / Unstructured Data (NLP & GenAI) Building lowlatency realtime systems using deep learning ...

Role: Data Scientist Location: Irving, TX - Fulltime Position Data Scientist with Generative AI ... Machine learning, NLP & deep learning: Strong understanding of supervised and unsupervised learning ...

Strong Time Series forecasting, ML, deep learning and standard statistical methods to evaluate models. Experience working on supply chain projects. We are seeking a highly skilled Data Scientist to ...

Stay up-to-date on state-of-the-art research in data science, deep learning, and security-specific AI to drive platform innovation. * Explore novel statistical methods and machine learning techniques ...

... on deep learning and LLM approaches โ€ข Stay abreast of leading-edge technologies in machine ... or data science: data analysis, algorithm design, model architecture specification, machine ...

Data Scientist Job Location: Holtsville, NY Duration: 6+ Months Responsibilities: - Design, build ... Technical Skills - Strong foundation in machine learning, deep learning, and AI frameworks ...

Data Scientist - AI/ML Focus Worksite: Onsite Monday-Thursday (Mandatory) - Houston, TX Must-Have ... Design, train, fine-tune, and evaluate machine learning and deep learning models--including LLMs ...

Work or educational background in one or more of the following areas: machine learning, computational linguistics, deep learning, ratification intelligence, data science and/or data analytic ...

Job Title: Data Scientist Job Location: Detroit, MI (Hybrid) Job Type: Contract * Develop and ... Strong experience with Machine Learning, Deep Learning, and NLP. * Proficiency in Python.

Senior Data Scientist Location: Taxes Experience: 12+ Years Job Summary We are seeking an ... Expertise in Machine Learning , Deep Learning , and Statistical Modeling * Experience with ...

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As a Data Scientist, you will be responsible for analyzing complex data sets to inform business ... Experience with TensorFlow or PyTorch for deep learning. * Understanding of MLOps for managing ...

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Weekend Data Scientist Deep Learning information

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$37.5K

$122.7K

$196.5K

How much do weekend data scientist deep learning jobs pay per year?

As of Jul 9, 2026, the average yearly pay for weekend data scientist deep learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Data Scientist Deep Learning vs Weekend Data Analyst?

AspectWeekend Data Scientist Deep LearningWeekend Data Analyst
Required CredentialsTypically requires a degree in Data Science, Computer Science, or related fields; knowledge of deep learning frameworksUsually requires a degree in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and basic analytics tools
Work EnvironmentOften involves working on complex machine learning models, coding in Python or R, and experimenting with neural networksFocuses on data cleaning, reporting, and visualization, often using Excel, Tableau, or Power BI
Employer & Industry UsageUsed in tech companies, research institutions, and AI-focused startupsCommon in finance, marketing, healthcare, and retail sectors

Weekend Data Scientist Deep Learning roles focus on developing advanced AI models and require programming skills, while Weekend Data Analysts handle data interpretation and reporting. Both roles are valuable but differ in technical complexity and industry application.

More about Weekend Data Scientist Deep Learning jobs
What cities are hiring for Weekend Data Scientist Deep Learning jobs? Cities with the most Weekend Data Scientist Deep Learning job openings:
What are the most commonly searched types of Data Scientist Deep Learning jobs? The most popular types of Data Scientist Deep Learning jobs are:
What states have the most Weekend Data Scientist Deep Learning jobs? States with the most job openings for Weekend Data Scientist Deep Learning jobs include:
Infographic showing various Weekend Data Scientist Deep Learning job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist - INDIA

Vytwo

Prosper, TX โ€ข On-site

Full-time

Re-posted 9 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 (37 years of experience) to join our team and work across two major data science domains:
  1. Structured Data (8090%) Predictive analytics, forecasting, cost estimation, likelihood modeling, and batchoriented machine learning pipelines.
  2. Text / Unstructured Data (NLP & GenAI) Building lowlatency realtime 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 realtime, lowlatency 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.