Senior Data Scientist at Engie Global Energy Management & Sales (Gems) in Houston, TX | USD131,000-200,790 | Kablio

Role

Description

hybrid modeling

ml pipeline

market forecasting

data analysis

price modeling

cloud deployment

Combine physical models with statistics and AI in creative ways to create models which are compute efficient while robust to extreme events and changes in the underlying system being modeled
Work with and contribute to internal custom machine learning pipeline and physical model development using Python packages and in-house libraries
Collaborate with the team to expand forecasting capabilities across various timescales and U.S. markets including PJM, SPP, and CAISO
Leverage data analysis to help identify areas for improvement of probabilistic price forecasts and develop experiments to help resolve and improve modeling efforts
Analyze, experiment, develop models, and evaluate models to help the company gather business intelligence and predict electricity prices
Work directly with the trading teams and Head of Market Analysis to create evaluation methodologies and assess quality of forecasts in terms of delivering clear signal for trading activities
Work with the development team to develop production level code to backtest and run models at scale in the cloud

Requirements

python

sql

machine learning

bachelor's

10+ years

probabilistic

Proficiency in a programming language such as Python (or similar) and SQL (or similar)
A minimum of ten (10) years working as a Data Scientist or a similar position
Ability to combine theory and data to develop experiment driven methodologies
This role is eligible for our hybrid work policy in our Houston, TX; Chicago, IL; and Broomfield, CO offices. For highly qualified candidates based in Pittsburgh, PA, a fully remote arrangement may be considered, provided the individual can travel to the Houston office for at least one week each month
Must be available to travel domestically up to 15% of the time and with the need for some overnight trips
Must be willing and able to comply with all ENGIE ethics and safety policies
Minimum of a Bachelor’s degree in a Science, Engineering, or Mathematics field
Proficiency with probabilistic thinking and evaluation
Ability to articulate experimentation methods, results, and conclusions clearly
Proficiency with correlated uncertainty quantification and statistical analysis
Proficiency with linear algebra and machine learning

Benefits

Information not given or found

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

this role is eligible for sponsorship.

Security clearance

Information not given or found

Company

Overview

#1 Rank

Global Energy Trading Leader

Recognized as the top performer in natural gas and LNG trading worldwide.

200,000+ Clients

Worldwide Customer Base

Serves over 200,000 clients by combining global reach with local expertise.

Its asset management arm secures and commercializes physical energy assets, boosting flexibility and revenue.
Through market access and risk services, it shields clients from volatility, deploying custom hedging and trading tools.
Its proprietary platform EGMA automates bilateral trades in seconds, integrating data, forecasts and ISO‑rated security.
Typical engagements include structuring PPAs, optimizing backup generation, managing certificate portfolios, and launching new energy-market platforms.

Culture + Values

Promotes a culture of performance, ethics, and integrity.
Committed to delivering value to clients through high-quality services.
Encourages innovation and flexibility in providing energy solutions.
Emphasizes teamwork, collaboration, and respect across all levels of the company.
Focuses on creating a sustainable and inclusive work environment.

Environment + Sustainability

2045

Net Zero Goal

Commitment to achieving Net Zero emissions by 2045.

Supports the transition to renewable energy and reducing carbon emissions across the energy value chain.
Prioritizes energy efficiency in both operational practices and customer solutions.
Promotes responsible sourcing and sustainable management of resources.
Is a signatory of the UN Global Compact, emphasizing sustainability in business practices.

Inclusion & Diversity

fosters an inclusive environment where diversity is valued and encouraged.
gender balance is a key priority, with efforts to increase female representation in leadership roles.
regular monitoring of diversity metrics to ensure consistent progress towards goals.
commitment to providing equal opportunities regardless of background or gender.

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Role

Description

hybrid modeling

ml pipeline

market forecasting

data analysis

price modeling

cloud deployment

Combine physical models with statistics and AI in creative ways to create models which are compute efficient while robust to extreme events and changes in the underlying system being modeled
Work with and contribute to internal custom machine learning pipeline and physical model development using Python packages and in-house libraries
Collaborate with the team to expand forecasting capabilities across various timescales and U.S. markets including PJM, SPP, and CAISO
Leverage data analysis to help identify areas for improvement of probabilistic price forecasts and develop experiments to help resolve and improve modeling efforts
Analyze, experiment, develop models, and evaluate models to help the company gather business intelligence and predict electricity prices
Work directly with the trading teams and Head of Market Analysis to create evaluation methodologies and assess quality of forecasts in terms of delivering clear signal for trading activities
Work with the development team to develop production level code to backtest and run models at scale in the cloud

Requirements

python

sql

machine learning

bachelor's

10+ years

probabilistic

Proficiency in a programming language such as Python (or similar) and SQL (or similar)
A minimum of ten (10) years working as a Data Scientist or a similar position
Ability to combine theory and data to develop experiment driven methodologies
This role is eligible for our hybrid work policy in our Houston, TX; Chicago, IL; and Broomfield, CO offices. For highly qualified candidates based in Pittsburgh, PA, a fully remote arrangement may be considered, provided the individual can travel to the Houston office for at least one week each month
Must be available to travel domestically up to 15% of the time and with the need for some overnight trips
Must be willing and able to comply with all ENGIE ethics and safety policies
Minimum of a Bachelor’s degree in a Science, Engineering, or Mathematics field
Proficiency with probabilistic thinking and evaluation
Ability to articulate experimentation methods, results, and conclusions clearly
Proficiency with correlated uncertainty quantification and statistical analysis
Proficiency with linear algebra and machine learning

Benefits

Information not given or found

Training + Development

Information not given or found

Interview process

Information not given or found

Visa Sponsorship

this role is eligible for sponsorship.

Security clearance

Information not given or found