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Temporary Computer Data Scientist Jobs in Houston, TX

Hexagon AB

Lead Data Scientist

Houston, TX · On-site

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD preferred) * Track record of deploying ML systems processing large-scale datasets with proper ...

Hp

AI Data Scientist - Enterprise AI

Spring, TX

$130K - $205K/yr

Bachelor's, Master's, or PhD in Computer Science, Data Science, Machine Learning, Artificial Intelligence, Statistics, Engineering, Mathematics, or a related field. * 3+ years of experience ...

bwp

Lead / Sr Analyst Data Scientist

Houston, TX · On-site

Bachelor's or Master's degree in Data Science, Computer Science, Engineering, Statistics, or a related field. * 3-5+ years of experience in applied data science, preferably in the energy, utilities ...

New

campus4tech

Lead Data Scientist

Houston, TX · On-site

Bachelor's Degree in science, engineering, computer science, mathematics, statistics, or related STEM field required. Master's Degree in Data Science preferred. Licenses/Certifications: (None ...

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All JobsComputer Data Scientist JobsTemporary Computer Data Scientist JobsTemporary Computer Data Scientist Jobs in Houston, TX

Temporary Computer Data Scientist information

See Houston, TX salary details

$43.9K

$157.6K

$232.5K

How much do temporary computer data scientist jobs pay per year?

As of Aug 23, 2026, the average yearly pay for temporary computer data scientist in Houston, TX is $157,588.00, according to ZipRecruiter salary data. Most workers in this role earn between $127,500.00 and $162,300.00 per year, depending on experience, location, and employer.

What is the difference between Temporary Computer Data Scientist vs Temporary Data Analyst?

AspectTemporary Computer Data ScientistTemporary Data Analyst
Required CredentialsBachelor's or higher in CS, Data Science, or related; often some experience with machine learningBachelor's in Statistics, Math, or related; proficiency in data visualization and basic analysis
Work EnvironmentTech companies, research labs, or consulting firms; project-based rolesBusiness, finance, marketing sectors; supporting decision-making processes
Employer & Industry UsageUsed across tech, healthcare, finance; often in innovative or R&D projectsCommon in corporate settings, retail, and marketing departments

Temporary Computer Data Scientists focus on advanced analytics, machine learning, and predictive modeling, requiring more technical expertise. Temporary Data Analysts primarily handle data collection, cleaning, and basic analysis to support business decisions. While both roles involve working with data, Data Scientists typically require stronger programming and statistical skills, whereas Data Analysts focus on reporting and visualization.

Can I get a temporary computer data scientist job with no experience?

Temporary computer data scientist roles typically require some experience in data analysis, programming, or related skills such as Python, R, or SQL. Entry-level positions may be available for those with relevant coursework, certifications, or strong analytical aptitude, but most employers prefer candidates with prior experience or demonstrated skills.

What cities near Houston, TX are hiring for Temporary Computer Data Scientist jobs?

Cities near Houston, TX with the most Temporary Computer Data Scientist job openings:

Temporary Computer Data Scientist jobs near you

Lead Data Scientist

Hexagon AB

Houston, TX • On-site

Full-time

Re-posted 1 hour ago

Job description

Lead Data Scientist
Job Location (Short): Houston, Texas-USA | Madison, Alabama-USA | Roanoke, Virginia-USA
Workplace Type: Remote
Req Id: 2289
Responsibilities
Octave's ETQ division is seeking a hands-on Data Scientist to build predictive models, implement Generative AI and Agentic AI features, and architect data-driven solutions for our document-based compliance management platform. This role requires a technical expert who can develop, deploy, and maintain ML systems in production environments.
  • Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and RAG architectures with vector databases for compliance document understanding
  • Design agentic AI systems that autonomously handle compliance workflows, document review, regulatory mapping, and multi-step reasoning tasks
  • Implement comprehensive LLM evaluation frameworks with automated pipelines, custom metrics, benchmark datasets, and safety guardrails ensuring regulatory compliance
  • Build end-to-end MLOps pipelines for model training, deployment, monitoring, versioning, and automated retraining with drift detection
  • Develop predictive models for compliance risk scoring, regulatory change impact, anomaly detection, and time-series forecasting
  • Write production-quality Python code for data processing, feature engineering, API development (FastAPI/Flask), and ETL/ELT workflows
  • Lead A/B experiments and product analytics to measure AI feature impact and drive data-driven decision-making
  • Create explainability frameworks (SHAP/LIME) and monitoring dashboards ensuring transparency and regulatory adherence
  • Collaborate with cross-functional teams to translate business needs into ML solutions and communicate insights to stakeholders

Python (5+ years): Production-level experience with Pandas, NumPy, scikit-learn, XGBoost, TensorFlow/PyTorch, Hugging Face Transformers, FastAPI/Flask, MLflow, and pytest
SQL: Advanced proficiency with complex queries, window functions, and optimization
Machine Learning & NLP: Strong foundation in supervised/unsupervised learning, deep learning, document understanding, text classification, and semantic analysis
Generative AI & LLMs: Hands-on experience with foundation models (GPT, Claude, Llama), prompt engineering, RAG architectures, and vector databases (Pinecone, Weaviate, Chroma)
MLOps & ModelOps: End-to-end experience with ML pipelines, experiment tracking (MLflow, W&B), model versioning, feature stores, drift detection, CI/CD for ML, and Docker containerization
LLM Evaluation: Experience with evaluation frameworks (RAGAS, DeepEval), custom metrics, benchmark datasets, and human-in-the-loop validation
Cloud & AWS: Experience with AWS services including SageMaker, Bedrock, S3, Lambda, EC2, and CloudWatch
Statistics & Experimentation: Strong foundation in statistics, A/B testing, causal inference, and experimental design
Visualization: Proficiency with Tableau, Power BI, or Python visualization libraries
Education / Qualifications
Experience & Education
  • 7+ years in data science, ML engineering, or related roles
  • 3+ years building NLP/generative AI applications and implementing MLOps in production
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or related field (PhD preferred)
  • Track record of deploying ML systems processing large-scale datasets with proper monitoring and governance

Preferred Qualifications
  • Experience with agentic AI frameworks (LangGraph, LangChain, AutoGen, CrewAI)
  • Knowledge of Life Sciences/regulated industries (FDA, EMA, ISO, GxP) and compliance management systems
  • Familiarity with big data tools (Spark, Databricks, Snowflake), orchestration (Airflow, Kubeflow), and monitoring tools (Datadog, Prometheus)
  • Experience with LLM fine-tuning, document processing libraries, multi-modal AI, or distributed training
  • Understanding of ML governance, bias detection, model risk management, and data privacy regulations (GDPR, CCPA, HIPAA)
  • Experience working in agile environments with Jira
  • AWS ML certifications or similar credentials

Key Competencies
  • Strong communication skills explaining complex models to technical and non-technical audiences
  • Ability to work independently and collaboratively in fast-paced environments
  • Proven ability to convert POCs into production-grade solutions
  • Understanding of ethical AI and building trustworthy, explainable systems for regulated environments

#LI-PB1 LI-Remote
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About Octave
Octave provides mission-critical software that empowers organizations to make informed decisions across every stage of the asset lifecycle - Design, Build, Operate and Protect - where performance, safety, and reliability are non-negotiable and failure is not an option.
Turning complex operational data into actionable intelligence, Octave connects expertise, real-world conditions and enterprise-scale insight to improve performance, resilience and incident response where it matters most.
Octave has approximately 7,200 employees in 45 countries. Learn more at octave.com and follow us on LinkedIn.
Why work for Octave?
All in. Always forward. That's the way we do things around here. We put trust in our people because we believe it's the best way to unleash potential, bring ideas to life, and keep moving ahead. And it's why we're committed to creating an environment that's truly supportive, providing you with the resources you need to support your ambitions, no matter who you are or where you are in the world.
Everyone is welcome
At Octave, we believe that diverse and inclusive teams are critical to the success of our people and our business. Here, everyone is welcome. As an inclusive workplace, we don't discriminate. In fact, we embrace differences and are fully committed to creating equal opportunities, an inclusive environment, and fairness for all.
Respect is the cornerstone of how we operate, so speak up and be yourself. You're valued here.
Recruitment Fraud Alert
Octave posts all official job opportunities on either https://careers.octave.com/ or https://www.octave.com/about/careers and communicates only from email addresses ending in @octave.com. We never request payment or personal banking information during recruitment. No offers will ever be extended without a proper interview via Teams or in person, never done over email alone. If you suspect fraud, it probably is, and contact us at careers@octave.com

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