Job Description:
1. Conduct data analysis using Python and related libraries to support business and operations objectives.
2. Work with time-series data from Canary Historian and other industrial data sources — extraction, cleaning, and preprocessing.
3. Build, deploy, and maintain analytics solutions and pipelines on Microsoft Azure (e.g., Azure Storage, Azure Data Factory, Azure Functions, Azure ML/App Services).
4. Perform advanced data manipulation and transformation using Pandas and NumPy, including handling large, high-frequency time-series datasets.
5. Build interactive dashboards and visualizations using the Dash framework, Django, or Streamlit (and/or Plotly, Matplotlib, Seaborn).
6. Execute exploratory data analysis (EDA) to identify trends, patterns, and anomalies in operational data.
7. Develop and support AI-assisted analytics use cases — such as anomaly detection, predictive maintenance, forecasting, and trend detection — using ML models and/or AI tools (including GenAI/LLM-based tools, Azure Foundry where relevant).
8. Explore opportunities to integrate AI-driven automation into dashboards and reporting workflows to reduce manual effort.
9. Collaborate with stakeholders across manufacturing and operations teams to understand requirements and deliver analytics solutions.
10. Present analysis results and insights clearly to both technical and non-technical audiences.
11. Write clean, efficient, and maintainable Python code.
12. Troubleshoot and debug issues across Python, data pipelines, Azure services, and database environments.
13. Stay current with industry trends and best practices in data science, analytics, AI, and cloud technologies.
EDUCATION AND EXPERIENCE REQUIRED :
· Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
· 1-3 years of professional experience in data science, data analytics, or a similar role.
· Proficiency in Python and familiarity with data analytics libraries (Pandas, NumPy, etc.).
· Hands-on knowledge or coursework/project experience with Microsoft Azure (storage, compute, data pipelines, or app deployment).
· Exposure to time-series data analysis and forecasting techniques.
· Solid understanding of statistical concepts and techniques (distributions, hypothesis testing, correlation, regression basics).
· Hands-on experience with the Dash framework, Django, or Streamlit for building interactive dashboards — able to build a working dashboard independently.
· Working understanding of AI/ML concepts and practical experience applying them to analytics problems (e.g., basic model building with Scikit-learn, or working with AI/GenAI tools, Azure Foundry and APIs).
· Curiosity and initiative to explore how AI can improve existing analytics and reporting processes.
· Familiarity with SQL and experience querying relational databases.
· Excellent problem-solving skills, attention to detail, and ability to debug issues independently.
OHMIUM CULTURE :
At Ohmium, you are expected to embody and champion our core cultural values:
Accountability: I own my tasks and execute on time.
Demonstrate strong accountability by owning deliverables and decisions, ensuring timely and consistent results.
Teamwork: I will not let other teams fail.
Takes ownership beyond own team to support cross-team success and prevent failures, thereby fostering a collaborative work environment.
Learning Mindset: I drive change and learn from mistakes.
Exhibits a strong growth mindset by proactively leading meaningful change and consistently learning from experience.
Winning Attitude: I compete to win.
Showing up every day with a strong perspective, to drive results and be the BEST in Green Energy.
We are seeking a motivated and technically strong Data Science Associate to join our team. The incumbent should have hands on experience working on with real-world industrial time-series data, building and deploying analytics solutions on Azure, and developing interactive dashboards. The role involves working with data from our Remote Monitoring Command Application Software (SCADA), with Canary Historian as the primary time-series data source,and owning analytics dashboards/pipelines end-to-end — from data extraction to deployment on Microsoft Azure.Ohmium is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Skills Required
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
- 1-3 years of professional experience in data science, data analytics, or a similar role.
- Proficiency in Python and familiarity with data analytics libraries such as Pandas and NumPy.
- Hands-on knowledge or coursework/project experience with Microsoft Azure, including storage, compute, data pipelines, or application deployment.
- Exposure to time-series data analysis and forecasting techniques.
- Understanding of statistical concepts including distributions, hypothesis testing, correlation, and regression basics.
- Hands-on experience with Dash, Django, or Streamlit for independently building working interactive dashboards.
- Working understanding of AI and machine learning concepts, with practical experience applying them to analytics problems.
- Curiosity and initiative to explore AI improvements to analytics and reporting processes.
- Familiarity with SQL and experience querying relational databases.
- Strong problem-solving skills, attention to detail, and ability to debug issues independently.
What We Do
Ohmium's mission is to accelerate the adoption of green hydrogen to decarbonize hard-to-abate sectors and enable a low-carbon future. Ohmium designs, manufactures and deploys modular, scalable proton exchange membrane (PEM) electrolyzer systems that enable cost-competitive green hydrogen production. Ohmium’s systems are vertically-stackable and integrate advanced power electronics, delivering superior value for a wide range of commercial and industrial applications in terms of safety, energy density, scalability and ramp rate. The human-scale electrolyzers are efficient to manufacture, quick to transport and easy to maintain. This versatility enables cost-effective plug-and-play operations that can scale rapidly. Ohmium has a global green hydrogen project pipeline across the U.S., Mexico, Europe and Asia.









