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Temporary Computer Data Scientist Jobs in Houston, TX

Beth Page tech

Data Scientist

Houston, TX · On-site

Master's/PhD in Computer Science, Data Science, or equivalent experience * 4-7 years of industry experience working with real-world datasets * Experience with Agile Scrum development methodology * C# ...

Munich Re

Data Scientist, AI

Houston, TX · On-site +1

Join our dynamic, centralized Data Science team as we execute our AI/ML roadmap! We focus on ... Master's degree in Business Analytics, Statistics, Computer Science, or Statistics/Math and ...

Hp

AI Data Scientist

Spring, TX · On-site

$130K - $205K/yr

PhD related to AI or a Master's degree in computer science or a related field and 5+ years of experience with GenAI and related technologies including machine learning. data analytics, and ...

Augment

Principal Scientist, Data

Houston, TX

$80 - $83/hr

D. in Computer Science, Data Science, Mathematics, Statistics, Engineering, or another quantitative discipline. * Experience using BI or model-monitoring tools (Power BI, Dash, Streamlit)

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 ...

Corva

Senior Data Scientist

Houston, TX · On-site

Master's or PhD in Computer Science, Statistics, Applied Mathematics, Data Science, Engineering, or a related quantitative field * 5+ years of experience building and deploying machine learning ...

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Temporary Computer Data Scientist information

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$43.9K

$157.6K

$232.5K

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

As of Aug 2, 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.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist, including at age 40. Success in data science depends on skills, experience, and continuous learning of tools like Python, R, and machine learning techniques, regardless of age. Many professionals transition into data science later in their careers and find opportunities with relevant certifications and a strong portfolio.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of the results come from 20% of the efforts or data. Data scientists often use this concept to focus on the most impactful features, data subsets, or models to improve efficiency and outcomes.

Is 30 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into the field later in life. Success depends on acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications, regardless of age.

Can I get a data scientist job with no experience?

Entry-level data scientist positions often require some knowledge of programming languages like Python or R, and familiarity with data analysis tools. While prior experience is preferred, candidates with relevant coursework, internships, or certifications can sometimes qualify for such roles.

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.

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

Data Scientist

Beth Page tech

Houston, TX • On-site

Contractor

Re-posted 9 days ago

Job description

Job Title: Data Scientist

Location: Houston, TX (Fulltime)

Environment: Standard, 5-days onsite

Job Description :

Must-Have (Technical Expertise & Core Responsibilities)

  • Data Science & Machine Learning:
    • Strong foundation in mathematics, statistics, and machine learning
    • Experience with exploring and extracting insights from multi-dimensional datasets
    • Proficiency in Python (clean, modular, well-documented code)
    • Experience with data visualization tools (D3.js, Bokeh, Plotly, or similar)
  • Domain Knowledge:
    • Ability to understand commodity trading/energy sector datasets and business needs
    • Experience translating complex models into actionable commercial insights

Core Responsibilities:

  • Develop and implement machine learning models to transform energy trading operations
  • Lead Proof of Concept (PoC) projects including:
    • Automated information extraction from unstructured data
    • Refinery outage prediction
    • Shipping cost forecasting
    • Gas network disruption analysis
  • Create data visualizations for both technical and non-technical stakeholders
  • Collaborate with domain experts to design user-friendly ML solutions
  • Work with Data Science and IT teams to leverage existing tools for business value

Qualifications & Skills:

  • Master's/PhD in Computer Science, Data Science, or equivalent experience
  • 4-7 years of industry experience working with real-world datasets
  • Experience with Agile Scrum development methodology
  • C# development experience (plus)

Nice-to-Have (Preferred Experience):

  • Background in commodity trading, energy markets, or financial services
  • Experience with big data technologies and cloud platforms
  • Knowledge of optimization techniques for business applications