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Day Learning Sciences Jobs in Spring, TX (NOW HIRING)

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

... day of crude oil and products and, at any time, has 250 ships transporting its cargoes. Vitol ... Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory ...

Vitol

Senior Machine Learning Engineer

Houston, TX

$117K - $154K/yr

... day of crude oil and products and, at any time, has 250 ships transporting its cargoes. Vitol ... Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

... day of crude oil and products and, at any time, has 250 ships transporting its cargoes. Vitol ... Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$116K - $154K/yr

They are seeking an experienced Machine Learning Engineer to join their data science and machine ... day-to-day workflows, and ensure outputs are robust, and trusted by end users. • Apply a broad ...

Beth Page tech

Data Scientist

Houston, TX · On-site

Standard, 5-days onsite : Must-Have (Technical Expertise & Core Responsibilities) * Data Science & Machine Learning: * Strong foundation in mathematics, statistics, and machine learning * Experience ...

Chevron

2026-2027 Earth Science Intern

Houston, TX · On-site +1

$10K/mo

Formal training + onthejob learning * Mentorship from experienced professionals * Multiple job ... Full year of service credit for each internship completion (must be re-employed within 365 days) If ...

WorkNovas LLC

Senior Data Scientist

Houston, TX · On-site

This requires that you have next to your knowledge of machine learning and/or statistics a good ... Work closely with the customer and the Product Owner day-to-day * Work in a highly-collaborative ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Houston, TX Environment: Standard, 5-days onsite : Must-Have (Technical Expertise & Core ... D. in Computer Science, ML, or related field. * 5-7+ years of industry experience in applying DNN ...

W3Global

Senior Data Scientist

Houston, TX · On-site

Houston, TX (Onsite - 5 Days) Type: Full-Time We are looking for a Senior Data Scientist with a ... Machine Learning (ML) Deep Learning (DL): Hands-on experience with: Generative AI (LLMs, RAG ...

Gallagher

Life Sciences - Vertical Leader

Houston, TX · Remote

Every day, we help clients navigate complexity, support recovery, and deliver outcomes that make a ... Career development opportunities and ongoing learning * A collaborative, people-first culture with ...

Sheldon ISD

7th Grade Science Teacher

Houston, TX · On-site

$42K - $52K/yr

Integrate technology and real-world applications into daily lessons to enhance student learning and ... Starting Salary $66,000 Works 187 Day Calendar *Position cannot be performed remotely Sheldon ISD ...

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All JobsDay Learning Sciences JobsDay Learning Sciences Jobs in Spring, TX

Day Learning Sciences information

See Spring, TX salary details

$41.8K

$59.4K

$73.4K

How much do day learning sciences jobs pay per year?

As of Aug 3, 2026, the average yearly pay for day learning sciences in Spring, TX is $59,354.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,600.00 and $66,300.00 per year, depending on experience, location, and employer.

What is day learning sciences?

Day Learning Sciences refer to the interdisciplinary field that studies how people learn throughout the day, typically focusing on formal and informal learning processes, cognitive development, and the design of effective educational environments. Professionals in this field analyze how learning occurs in various settings—such as classrooms, workplaces, or everyday life—and apply research to improve teaching methods and educational technology. The goal is to enhance learning outcomes by understanding and optimizing how knowledge is acquired, retained, and applied.

How does a day learning sciences professional typically collaborate with teachers and school administrators to implement effective educational strategies?

Day Learning Sciences professionals often work closely with teachers and school administrators to analyze student data, design evidence-based learning interventions, and provide training on new instructional methods. They may facilitate workshops, observe classrooms, and offer feedback to ensure best practices are consistently applied. Open communication and teamwork are essential, as these professionals act as a bridge between educational research and classroom practice. This collaborative approach helps create an environment where both educators and students can thrive.

What is the difference between Day Learning Sciences vs Day Education Specialist?

AspectDay Learning SciencesDay Education Specialist
CredentialsTypically requires a degree in education, psychology, or related fields; certifications in instructional design or learning technologies are commonRequires a degree in education or related fields; certifications in teaching or curriculum development are often preferred
Work EnvironmentWorks primarily in educational institutions, corporate training, or online learning platformsWorks mainly in schools, training centers, or educational organizations
Employer & Industry UsageUsed by educational institutions, e-learning companies, and corporate training providersEmployed by schools, educational agencies, and training organizations

Day Learning Sciences focuses on applying scientific principles to design effective learning experiences, often involving research and technology. In contrast, Day Education Specialists typically implement and deliver educational programs directly to learners. Both roles require educational credentials but differ in their focus on research versus direct instruction.

What are the key skills and qualifications needed to thrive as a learning sciences specialist?

To thrive as a Learning Sciences Specialist, you need a deep understanding of educational psychology, instructional design, and research methodologies, often supported by an advanced degree in learning sciences or a related field. Familiarity with learning management systems (LMS), data analysis tools, and qualitative/quantitative research software is typically required. Strong analytical thinking, collaboration, and communication skills help you design effective learning interventions and work with diverse stakeholders. These competencies are crucial for developing evidence-based educational solutions that improve learning outcomes.
What cities near Spring, TX are hiring for Day Learning Sciences jobs? Cities near Spring, TX with the most Day Learning Sciences job openings:
Day Learning Sciences jobs near you

Senior Machine Learning Engineer

Vitol

Houston, TX • On-site

$117K - $154K/yr

Full-time

Re-posted 27 days ago

Job description

Company Description
Vitol is an energy and commodities company with revenues of $400 billion in 2023; its primary business is the trading and distribution of energy products globally - it trades over seven million barrels per day of crude oil and products and, at any time, has 250 ships transporting its cargoes.
Vitol's clients include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves clients from some 40 offices worldwide and is invested in energy assets globally including 16mm3 of storage, 480kbpd of refining capacity, and 7,000 service stations. To date, we have committed over $2.5 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world. Learn more about us here.
This Role is located in Houston, TX - In office 5x a week
Job Description
As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and technologies.
The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models.
The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the 'art of the possible'.
Core Responsibilities include:
  • Design, develop, and deploy end-to-end machine learning and data science solutions across our wider business activities (including trading, operations, and support functions) - from raw data ingestion through to production-grade models and monitoring
  • Drive adoption and development of the firm's internal GenAI chat platform as one of the technical leads, extending its capabilities through new integrations, data connectors, and domain-specific prompt engineering; work closely with trading desks and operational teams to identify high-value use cases, embed the tool into day-to-day workflows, and ensure outputs are robust, and trusted by end users.
  • Apply a broad range of modelling techniques - including time-series forecasting, NLP, classification, and generative AI - to commodity pricing, supply/demand signals, trade flow analysis, and operational optimization problems
  • Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory analysis, feature engineering, model selection and validation, deployment, and ongoing performance monitoring
  • Build and maintain robust, well-tested, production-quality code; contribute to shared infrastructure including ML pipelines, data orchestration, and model serving layers
  • Integrate ML and GenAI outputs into existing trading systems, dashboards, and workflows; work with software engineers to ensure reliable, scalable adoption across the business
  • Communicate analytical findings and model outputs clearly to non-technical stakeholders; present results, assumptions, and limitations in a manner that supports confident commercial decision-making
  • Actively participate in code reviews, experiment design, and tooling decisions; mentor colleagues and help raise the overall standard of analytical and engineering practice across the team

Qualifications
  • Master's degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
  • Fluency in Python for both data science and engineering purposes: clean, modular, well-documented code, with strong understanding of software engineering best practices including version control, testing, and code review
  • 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production environments
  • Demonstrable experience applying a broad range of ML methodologies (supervised and unsupervised learning, time-series modelling, NLP/LLMs, optimization) to real-world business problems
  • Strong proficiency with ML frameworks (e.g. PyTorch, scikit-learn, Transformers) and experience building or consuming LLM-based pipelines and GenAI applications
  • Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization (Docker/Kubernetes), CI/CD, data pipeline orchestration (e.g. Airflow, Dagster), and model serving
  • Strong analytical and problem-solving ability: capable of defining and scoping open-ended problems, proposing sound methodological approaches, and defending modelling choices with rigorous reasoning
  • Excellent written and verbal communication skills, with the confidence to present model outputs, caveats, and commercial implications clearly to non-technical audiences including traders and senior management
  • Genuine intellectual curiosity about commodities markets, global energy flows, and the commercial dynamics of trading; willingness to develop domain knowledge as part of the role

Desirable Experience
  • Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts
  • Experience surfacing ML outputs through interactive tools (e.g. Dash, Streamlit, or similar) and presenting use cases to non-technical audiences, including traders and senior management
  • Time-series modelling in a trading or financial context, including both ML-based and econometric approaches (e.g. ARIMA, cointegration, regime-switching models)
  • Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines

Additional Information
Personal Characteristics
  • A self-motivated individual who thrives on seeing the results of their work make an impact in the business
  • Pragmatic and delivery-focused: comfortable navigating ambiguity, balancing rigor with speed, and making sound judgements under uncertainty
  • Methodical and detail-oriented: rigorous in experimental design, data validation, and code quality, with a disciplined approach to documenting assumptions and results
  • Resourceful, able to think creatively and adapt in a dynamic environment
  • Team player, with an open non-political style and a high level of integrity
  • Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world's energy flows

Work Environment
  • This job operates in a professional office environment. Because of the collaborative, fast-paced, and high energy nature of our business, Vitol requires team members to work from our fully-equipped office.

What we offer
  • Competitive salary and benefits package
  • Large diversity of projects with real-world impacts on a truly global scale
  • Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly
  • Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva)
  • A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit
  • Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry
  • Strong management commitment to incorporating machine learning into the future of Vitol's operations

All your information will be kept confidential according to EEO guidelines.

Apply