职位描述
As an integral part of Hanwha Energy USA's Commodities team, the Data Scientist will oversee the entire data science pipeline for wholesale power and gas market applications including price forecasting, congestion analysis, load forecasting, and trading algorithms. This will encompass R&D, model development, pre- and post-model analytics, model deployment, and management of the ML model library. This role will leverage the latest AI/ML modeling techniques to directly impact the company's ability to make informed decisions, optimize operations, mitigate risks, and drive business growth.
The role requires a self-motivated, dedicated, and responsible individual with the ability to perform well under pressure collaboratively with a team of highly analytical and quantitative talent. Along with deep expertise in AI/ML modeling, the candidate should possess a solid understanding of power and gas market fundamentals - with particular emphasis on ERCOT and PJM markets - and emerging trends in wholesale energy.
The position will be based out of the Hanwha Energy USA Houston office, and the ideal candidate will be within commutable distance to the Houston office location.
Responsibilities
- As part of Hanwha Energy USA's Commodities team, this position will play a pivotal role in developing innovative solutions to wholesale power and gas analytical needs - including price forecasting, congestion analysis, and trading algorithms - by applying state-of-the-art machine learning and predictive modeling techniques
- Responsible for coordinating the entire ML life cycle including pre-model analytics, model selection, feature engineering, post model evaluation, and model refinements across power and gas market applications
- Develop, maintain, and continuously improve production-grade forecasting and analytics models for wholesale power and gas markets, with a focus on ERCOT and PJM
- Build and interpret models that capture the key drivers of power and gas price formation - including generation dispatch, transmission congestion, fuel prices, weather, load patterns, and market participant behavior
- Coordinate model deployment efforts including integration into downstream business processes, tracking performance metrics, and maintaining model health in cloud environments
- Develop a comprehensive data visualization layer to enable intuitive understanding of analytical drivers by business stakeholders
- Working closely with the technology team and leveraging vast amounts of proprietary and market data, develop ways to extract business intelligence and actionable insights that can have a meaningful impact on the company's bottom line
- Communicate technical details of the modeling to key stakeholders and partners to drive impact and facilitate decision making
Required Competencies
- Analytical - Proven problem-solving capability with strong analytical skills including statistical analysis.
- Stakeholder Engagement - Understands the importance of seeking out relationships and working with others toward a shared goal.
- Effective Communication - Strong verbal and written communication skills.
- Agility - Demonstrate willingness to modify position as needed to meet the needs of the business.
Required Qualifications
- Strong technical knowledge in deep learning and time series modeling - including GBM, LSTM, Transformer architectures, CNN, VAE, GAN and GNN - with demonstrated application in power or gas market contexts
- Minimum 3 years (Data Scientist) or 7 years (Senior Data Scientist) of industry experience applying modeling techniques in successful commercial energy applications
- Solid understanding of ERCOT and PJM market fundamentals - including wholesale price formation, transmission congestion, nodal pricing, generation dispatch, and fuel market dynamics
- Understanding of transmission congestion in ERCOT and PJM - including how constraints bind, how congestion propagates across the network, and how shadow prices reflect the cost of binding constraints
- Experience with Large Language Models (LLMs) - including practical application of LLMs for market intelligence, analytical summarization, retrieval-augmented generation (RAG), or workflow automation in a commercial setting
- An advanced degree, preferably Ph.D, in Engineering, Math, Physics, or a related field of study
- Strong problem-solving skills along with the ability to intuitively explain complex technical concepts to business stakeholders
- Strong knowledge in programming (Python, SQL), visualization tools (Plotly, PowerBI), ML packages (PyTorch, TensorFlow) and hyperparameter tuning (Optuna)
- Experience with cloud platforms (Azure or AWS) and MLOps practices - including model deployment, pipeline orchestration, experiment tracking, and model monitoring in production environments
- Proven track record in managing complex projects and leading cross-functional teams
- Excellent interpersonal skills with capability to work collaboratively with technical and non-technical teams
- Eligible to work in the USA for any employer without sponsorship
Preferred Qualifications
- Experience with Graph Neural Networks (GNN) or graph-based modeling approaches - a significant differentiator for this role given the team's current AI initiative roadmap
- Direct experience in wholesale power or gas trading environments - understanding of how analytical outputs translate into commercial trading and hedging decisions
- Familiarity with ERCOT-specific datasets - nodal prices, shift factor matrices, constraint shadow prices, bid/offer disclosures, and generation outage feeds
- Experience with production cost modeling software such as DAYZER, PLEXOS, Aurora XMP, or PROMOD
- Familiarity with gas market fundamentals - pipeline flows, basis differentials, storage dynamics, and their interaction with power price formation
- Experience with MLOps tooling - MLflow, Airflow, Kubeflow, Azure ML, or AWS SageMaker - for production model lifecycle management
Compensation: $140,000 - $180,000 salary
Attention external recruitment firms, we will not accept any unsolicited resumes at this time. Please do not contact any internal member of our company to discuss the position or to solicit candidates.
Hanwha Energy USA provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.
薪资与福利
职位详情
关于 Hanwha Energy USA
公司概况
Hanwha Energy USA,Hanwha集团旗下Hanwha Energy Corporation的全资子公司
总部美国德克萨斯州休斯顿
成立时间2017年
规模近年来约有500名员工(来源:linkedin.com)
业务范围
Hanwha Energy USA作为Hanwha Energy在美国的投资与孵化部门,专注于可再生能源、能源支持基础设施及涵盖整个能源价值链的新兴技术。其业务涵盖公用事业规模的太阳能和电池储能系统(BESS)开发、零售电力服务、燃气发电解决方案以及数据中心能源基础设施(来源:hanwhaenergyusa.com)。公司业务划分为多个板块,包括专注太阳能和BESS项目的Hanwha Renewables,提供超大规模及企业数据中心综合能源解决方案的Hanwha Data Centers,面向电力市场放开地区提供零售电力的Chariot Energy,以及负责调度发电的Hanwha Gas Power Solutions(来源:hanwhaenergyusa.com)。Hanwha Energy USA在公用事业规模太阳能和储能资产的项目开发、融资、所有权及运维方面拥有深厚专业经验,与北美各地的土地所有者、社区和投资者建立合作(来源:linkedin.com)。此外,公司正拓展天然气发电及数据中心能源解决方案业务,包括面向超大规模数据中心的双向电表服务(来源:greenhouse.io)。
项目与业绩
Hanwha Energy USA已签署近2GW的购电协议,并在美国拥有超过8GW的开发管线(来源:linkedin.com)。其活跃的太阳能项目遍布加利福尼亚、德克萨斯、亚利桑那和纽约等关键州,重要里程碑包括内华达州402MW的太阳能项目以及在内华达和亚利桑那州出售了1,661MW的太阳能和储能项目(来源:hanwha-energy.com,hanwha-energy.com)。位于德克萨斯的Oberon 1A太阳能电站体现了其在美国太阳能领域的实力(来源:hanwha.com)。在储能方面,Hanwha Energy USA拥有5.7GW的储能系统管线,推动大型太阳能加储能项目的发展(来源:hanwha-energy.com)。其零售能源品牌Chariot Energy在德克萨斯积极服务客户,并与Sam Houston Race Park建立了官方电力供应合作关系(来源:news.hanwhaenergyusa.com)。
最新动态
2026年1月,Hanwha Energy USA将174 Power Global与Hanwha Renewables合并,统一以Hanwha Renewables品牌打造开发平台,加速美国公用事业规模太阳能光伏和BESS项目的推进,提升规模和技术能力,同时保持现有合作伙伴关系(来源:linkedin.com,linkedin.com)。公司还宣布计划收购德克萨斯一座燃气发电厂,标志着向调度发电领域的战略扩展(来源:news.hanwhaenergyusa.com)。此外,Hanwha Energy USA于2024年5月在德克萨斯乔治敦开设全球运维远程操作中心,支持卓越运营(来源:hanwha-energy.com)。2026年的招聘重点聚焦天然气发电和数据中心能源基础设施,包括超大规模数据中心解决方案(来源:greenhouse.io,greenhouse.io)。
工作环境
Hanwha Energy USA招聘涵盖开发、工程、商品、数据科学、运营、零售电力及数据中心相关能源基础设施等多领域职位(来源:greenhouse.io,greenhouse.io)。数据科学家职位侧重于批发电力和天然气市场分析、预测、拥堵分析及交易算法,工程领导岗位则负责新电厂、数据中心分布式能源系统、氢能设施及商用和工业客户的技术评估(来源:greenhouse.io,greenhouse.io)。公司在休斯顿设有总部及主要招聘基地,同时在加利福尼亚尔湾区的欧文设有办公地点(来源:hanwhaenergyusa.com,linkedin.com)。Hanwha Energy USA的企业文化融合了传统项目开发专业知识与围绕数据中心和燃气发电构建创新平台的理念,强调技术深度、市场分析、工程优化及跨职能协作(来源:greenhouse.io,greenhouse.io)。高级技术岗位的薪酬范围包括数据科学家14万至18万美元,资深工程总监19万至25万美元,体现了具有竞争力的薪资水平(来源:greenhouse.io,greenhouse.io)。零售能源品牌Chariot Energy则突出以消费者为中心的文化,提供创新的产品结构、具有竞争力的价格及屡获殊荣的客户服务(来源:hanwhaenergyusa.com)。
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