HYDERABAD · FULLTIME
Data Analyst II
Schneider Electric
Hyderabad · onsite · Posted 13d ago
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Undisclosed4–6 yrsfulltimeHyderabad
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Section · 01
About this role
Job Summary
Key Responsibilities
Required Qualifications
Technical Skills
Preferred Experience
Ownership Growth Expectations
Responsibilities vs. Competencies Matrix
Must-Have Skills
Good-to-Have Skills
Soft Skills
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
We are looking for a hands-on Data Scientist Python Developer with around 5 years of experience in building, deploying, and maintaining machine learning models and data-driven applications. The role focuses on independent delivery of ML features end to end, working closely with senior data scientists, architects, and product owners.
Key Responsibilities
- Develop, train, and evaluate machine learning models for business and industrial use cases.
- Build Python applications, REST APIs, and data pipelines to operationalize models.
- Develop forecasting, anomaly detection, and predictive analytics models.
- Deploy models using Docker and CI/CD; support model monitoring and retraining.
- Perform data exploration, cleansing, and feature engineering on structured and time-series data.
- Work with product owners and stakeholders to understand requirements and present results.
- Participate in code reviews and support junior team members.
Required Qualifications
- Bachelor's or Master's Engineering degree in Computer Science, Data Science, Engineering, or related field.
- 4-6 years of experience in Data Science, Machine Learning, and Python development, with at least 2 models deployed to production.
Technical Skills
- Programming: Python, SQL; FastAPI or Flask
- ML Libraries: Scikit-learn, XGBoost, Pandas, NumPy; TensorFlow or PyTorch
- Data Engineering: Spark, Airflow (Kafka, Databricks - exposure)
- Cloud: Azure, AWS, or GCP (at least one, hands-on)
- MLOps: Git, Docker, MLflow, CI/CD (Kubernetes - exposure)
- Visualization: Power BI, Tableau, or Plotly
Preferred Experience
- Exposure to Industrial AI, Manufacturing, Energy, or IoT data (sensor / time-series).
- Working knowledge of GenAI, LLMs, RAG, or Agentic AI frameworks.
Ownership Growth Expectations
- Own ML features/modules end to end with minimal supervision.
- Contribute to design discussions; follow engineering and data science best practices.
- Share knowledge within the team and guide junior members.
- Continuously upskill in emerging AI/ML technologies.
Responsibilities vs. Competencies Matrix
- ML Model Development - Key Competencies: Machine Learning, Statistics, Feature Engineering, Model Evaluation
- Python Application Development - Key Competencies: Python, REST API Development, Clean Code, Unit Testing
- Data Pipeline Engineering - Key Competencies: ETL/ELT, SQL, Spark, Airflow (Kafka exposure)
- MLOps Deployment - Key Competencies: Docker, CI/CD, MLflow, Model Monitoring
- Cloud Solution Development - Key Competencies: Hands-on with Azure, AWS, or GCP services
- Stakeholder Engagement - Key Competencies: Communication, Requirement Understanding, Presenting Insights
- Team Collaboration - Key Competencies: Peer Reviews, Knowledge Sharing, Guiding Junior Members
Must-Have Skills
- 4-6 years of experience in Data Science and Python development
- Strong Python and SQL; hands-on with Scikit-learn and TensorFlow or PyTorch
- Experience deploying at least one ML model to production
- Hands-on experience with one cloud platform (Azure, AWS, or GCP)
- Basic data engineering skills (ETL, Spark or Airflow)
- Good communication and collaboration skills
Good-to-Have Skills
- GenAI, LLMs, RAG, or Agentic AI exposure
- Industrial AI, Manufacturing, Energy, or IoT domain knowledge
- Kubernetes, Kubeflow, Databricks, Delta Lake
- Predictive Maintenance or Digital Twin projects
- Computer Vision or Reinforcement Learning projects
- Structured problem-solving and strong analytical thinking
- Takes ownership of assigned deliverables and quality of outcomes
- Collaborates effectively in cross-functional, agile teams
- Adapts to changing priorities and learns quickly
- Focuses on delivering measurable business value
Soft Skills
- Analytical thinking, clear communication, teamwork, problem-solving, and eagerness to learn
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
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Section · 02
Skills
AutomationAgileapisdata analystComputer Visionai frameworkscloud platformamazon web servicesapache airflowAnalyticsClean CodeAnomaly DetectionData EngineeringcloudCyber SecurityApplication DevelopmentcomplianceMicrosoft AzureData PipelineArtificial Intelligence
Section · Company
About Schneider Electric
Schneider Electric
Industrial Automation
37.0k+
employees
1999
27 years old
Paris
France
About
Global leader in energy management and automation, driving sustainability and efficiency with €38.15 billion in 2024 revenue, innovating for a more sustainable future worldwide.
Industries
Industrial AutomationArchitecture & Interior Design
Employee ratings
5,153 reviews
4.1/ 5
Culture
4.0
Career growth
3.3
Work-life
4.0
Employees rate it well for
Work Life Balance535Work Culture444Salary408Work Environment315Learning313
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