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.

Skills:-

Education: -

Ohmium is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.