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Internship Predictive Modeling Jobs in Texas (NOW HIRING)

Cenergistic LLC

Control Tech - Dallas, TX

Dallas, TX · On-site

... predictive modeling, anomaly detection, and utility analytics across every meter and system. For 13 ... Internship experience in HVAC or building systems. * Interest in energy conservation and ...

Cenergistic

Control Tech - Dallas, TX

Dallas, TX · On-site

... predictive modeling, anomaly detection, and utility analytics across every meter and system. For 13 ... Internship experience in HVAC or building systems. * Interest in energy conservation and ...

Aivra Health LLC

AI/ML Engineer

Dallas, TX · On-site

Implement predictive models and recommendation/classification systems. * Work with Generative AI ... internships, academic projects, research, GitHub repositories, or professional experience ...

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Internship Predictive Modeling information

What is the difference between Internship Predictive Modeling vs Data Analyst?

AspectInternship Predictive ModelingData Analyst
Required CredentialsTypically pursuing or recent graduate in data science, statistics, or related fieldsOften holds a degree in statistics, mathematics, or related disciplines
Work EnvironmentInternship setting, often in tech, finance, or marketing companiesFull-time or part-time roles in various industries including finance, healthcare, and retail
Employer & Industry UsageUsed in companies focusing on developing predictive models and machine learning applicationsCommon in organizations analyzing data trends, reporting, and decision-making

Internship Predictive Modeling focuses on developing and applying models to forecast outcomes, often as part of an internship program. Data Analysts interpret data, generate reports, and support business decisions. While both roles require analytical skills, predictive modeling emphasizes machine learning and statistical modeling, whereas data analysis centers on data interpretation and visualization.

Internship Predictive Modeling jobs near you

Data Science Machine Learning Internship (Summer 2027)

Castleton Commodities International LLC

Houston, TX • On-site

Full-time

Re-posted 11 days ago

Job description

Application Deadline: September 1, 11:59pm EST

Program Summary - Commercial Technology Internships

Company Overview:

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the Company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in, and develop, select commodity infrastructure assets. Our strategically integrated platform has generated strong risk-adjusted returns for our investors since our formation.

Position Overview:

CCI is developing a leading-edge Data Science platform, as staying at the forefront of data management and analytics is essential to our investment strategy. We are looking for motivated and detail-oriented Machine Learning Interns with a strong interest in quantitative analysis, particularly time series forecasting to join our Global Data Science team in Stamford, CT, Houston, TX, or New York City offices. Our Machine Learning Internship provides a unique opportunity to work with fundamental market data, generating insights that support our commercial trading business. You will be responsible for analyzing time series data related to market fundamentals in the Power, Natural Gas, and Oil sectors, helping to identify key supply and demand drivers. These insights will play a vital role in forecasting price movements and supporting risk management decisions.

Responsibilities:

  • Apply mathematical and statistical knowledge to enhance existing machine learning applications and explore new solutions.
  • Work closely with Data Scientists, Analysts, and Traders to design, implement, and optimize machine learning models for time series forecasting, including ARIMA/SARIMA, gradient boosting methods (e.g., XGBoost), LSTM networks, and linear regression-based approaches.
  • Assist in designing and implementing end-to-end data ingestion processes, ensuring seamless data flow to investing teams.
  • Work with desk heads, traders, and analysts to understand current data architecture, investment processes, and functional requirements for data science analysis.
  • Contribute to identifying and back-testing new data sets, leveraging machine learning techniques to drive insights.
  • Conduct ad hoc research on emerging project topics, including energy fundamental data, analytics trends, and best practices in big data and artificial intelligence.

Qualifications:

  • Currently pursuing a Bachelor's Degree or higher in Mathematics, Statistics, Physics, Computer Science or related technical field with a focus in Machine Learning.
  • Expected graduation date of Winter 2027 or Spring/Summer 2028.
  • Experience applying machine learning techniques such as regression, time series forecasting, deep learning, reinforcement learning, or predictive modeling to solve problems involving complex data patterns and market dynamics.
  • Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.)
  • Ability to communicate and interact with a wide range of users, from very technical to non-technical backgrounds.
  • Strong analytical skills with demonstrated attention to detail.

Apply