Associate, Data Scientist

Overview

Data Science Associate role at Ohmium working with real-world industrial time-series data from SCADA and Canary Historian, building and deploying analytics solutions on Microsoft Azure and developing interactive dashboards.

What you'll do

• Conduct data analysis using Python and related libraries to support business and operations objectives.
• Extract, clean and preprocess time-series data from Canary Historian and other industrial data sources.
• Build, deploy and maintain analytics solutions and pipelines on Microsoft Azure (e.g., Azure Storage, Azure Data Factory, Azure Functions, Azure ML/App Services).
• Perform advanced data manipulation and transformation using Pandas and NumPy, including handling large, high-frequency time-series datasets.
• Build interactive dashboards and visualizations using the Dash framework, Django, or Streamlit (and/or Plotly, Matplotlib, Seaborn).
• Execute exploratory data analysis (EDA) to identify trends, patterns, and anomalies in operational data.
• 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).
• Explore opportunities to integrate AI-driven automation into dashboards and reporting workflows to reduce manual effort.
• Collaborate with stakeholders across manufacturing and operations teams to understand requirements and deliver analytics solutions.
• Present analysis results and insights clearly to both technical and non-technical audiences.
• Write clean, efficient, and maintainable Python code.
• Troubleshoot and debug issues across Python, data pipelines, Azure services, and database environments.
• Stay current with industry trends and best practices in data science, analytics, AI, and cloud technologies.

What you'll need

• 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.