Data Scientist

Rapinno Tech; Houston (TX); On-site; USD 90,000 - 120,000; Full time

Job summary

A data-focused tech company in Houston is looking for a Data Scientist to join their team. You will apply statistical machine learning models to forecast energy market data. The role involves analyzing energy time series, building predictive models, and collaborating closely with data engineers and scientists. Ideal candidates have a background in oil, gas, or energy, along with proficiency in Python or R, and cloud computing experience. Essential skills include strong communication and problem-solving abilities, with at least 2 years in relevant areas.

Qualifications

• 2+ years of experience deploying machine learning models in production.
• 3+ years of experience with supervised and unsupervised machine learning models.
• Experience with cloud computing platforms, preferably AWS.

Responsibilities

• Analyze energy time series and summarize the statistical properties.
• Build predictive models for day-ahead consumption data.
• Evaluate and compare model performance against existing models.
• Deploy and document research results.

Skills

Proficiency with Python

Proficiency with R

SQL

Statistical analysis

Machine learning

Communication skills

Data analysis

Tools

Pandas

Sklearn

NumPy

AWS

Azure

Spark

TensorFlow

Keras

PyTorch

Job description

Note: Need Only US Citizen, Green Card, EAD-GC, J2 EAD, H4 EAD, L2 EAD, and TN Visa.

Job Title: Data Scientist
Location: Houston, TX
Duration: 06+ Months Contract

Note:

Oil, Gas and energy background in Preferred

Job Description

You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets. The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues.

Specific Responsibilities

• Analyze energy time series and summarize the statistical properties of energy signals
• Build predictive models and forecast signals for day‑ahead consumption data
• Evaluate the performance and compare the results with existing models
• Deploy the best model and document the result of this research

Business Skills

• Excellent verbal, written, and interpersonal communication skills
• Strong understanding of the product development lifecycles
• Strong understanding of software development, testing and integration methodologies
• Personal effectiveness/credibility
• Strong problem solving and analysis skills

Technical Skills

• Proficiency with Python or R, SQL and familiarity with working in big data environments (2 years minimum)
• At least 2+ years of experience of deploying machine learning models and frameworks in production
• At least 3 years of experience with supervised and unsupervised machine learning models (regressions, gradient boosted methods, SVMs, random forests, clustering)
• Familiar with Python packages such as Pandas, Sklearn, NumPy, etc.
• Deep learning (CNN, RNN, LSTM) and framework libraries (e.g., Keras, TensorFlow, PyTorch) and graph neural networks
• Evaluation and hypothesis testing
• At least 3 years of experience with cloud computing platforms such as AWS, Azure (preferably AWS)
• Experience with standard CI/CD build and deployment pipeline technologies
• At least 2 years of experience in distributed computing frameworks such as Spark or PySpark