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Data Scientist

Role overview

Qualifications

  • Oil, Gas and energy background in Preferred
  • Proficiency with Python or R, SQL
  • At least 2+ years of experience of deploying machine learning models and frameworks in production
  • At least 3 years of experience with Cloud computing platforms such as AWS, Azure

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

About the company

Rapinno Health Care logo

Rapinno Health Care

Contract Research Organizations (CRO)

At Rapinno Health Care, our expertise is helping healthcare organizations find a seamless workforce solution that aligns with our client's business strategies and overall staffing goals. We pride ourselves on building positive relationships to ensure that everyone involved brings added value to our customers and the patients they serve. Backed with a rich experience of Rapinno Tech, Rapinno Health Care believes that a successful healthcare organization must run like any efficient and successful business. To do this, you need to have the best talent and create synergies between maintainers, administrators, and organizational policy to create a recipe for success.

Company details

Company typeSME
IndustryContract Research Organizations (CRO)
Company size11 - 50

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Job description

VERY URGENT AND IMMEDIATE NEED.

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 include:

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:

Experiences in both 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 library (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)

Standard concepts and technologies used in CI/CD build and deployment pipelines.

At least 2 years of experience in distributed computing frameworks such as Spark or Pyspark is desirable.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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