Data Scientist Associate

Job Summary :

We are seeking a motivated and technically strong Data Science Associate to join our team. This role is suited for an early-career professional with 1-3 years of experience who is comfortable working hands-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.

Roles and Responsivities :

• Conduct data analysis using Python and related libraries to support business and operations objectives.
• Work with time-series data from Canary Historian and other industrial data sources extraction, cleaning, and preprocessing.
• 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.

Preferred candidate profile

• 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.