Senior Data Scientist I

Schneider Electric

Bengaluru, INonsitePosted Jun 23, 2026

Skills

scikitlearndatabricksmatplotlibtensorflowtimeserieslangchainpytorchdockerpandasplotlygithubpythonopenaiflaskazurenumpykerascicdnaturallanguageprocessingllmml

About the role

Job Description:

We are looking for a passionate Senior Data Scientist with strong hands-on expertise in

AI/ML, Generative AI, Computer Vision, LLMs, Agentic AI, and Edge AI to join our team. The

role will focus on identifying, designing, and enabling AI-driven capabilities across

industrial automation platforms, helping drive intelligent decision-making, operational

efficiency, and next-generation smart manufacturing solutions across edge and cloud

environments.

Key Responsibilities

Machine Learning and Model Analysis

Apply machine learning, statistical, and experimental design techniques to assess

model behavior and performance in industrial and real-time operational

environments.

Evaluate the impact of training methodologies, industrial data sources

(sensor/PLC/SCADA streams), model architectures, and deployment strategies

across edge and cloud.

Review and assess third-party or open-source models, runtimes, and tools from

perspectives of safety, robustness, latency, reliability, and end-to-end industrial

integration.

Research and Prototyping

Drive research, experimentation, and prototyping of advanced AI/ML techniques

tailored for industrial automation use cases across edge and cloud platforms.

General

Explore innovative approaches in areas such as anomaly detection, predictive

maintenance, vision-based inspection, hallucination detection, explainability, and

industrial AI trustworthiness.

Lead proof-of-concepts (PoCs) and experimental studies to evaluate readiness of

new AI methods, models, and metrics for industrial deployment.

Collaborate with engineering teams to transition successful prototypes into

scalable, production-grade industrial solutions.

Design scalable system architectures for complex AI/LLM-driven industrial

applications, ensuring seamless integration with OT systems, data pipelines, and

enterprise IT systems.

Collaboration, Documentation, and Governance Support

Collaborate closely with Line-of-Business (LOB), product, and platform teams to

operationalize AI solutions in industrial automation products.

Guide and support teams in integrating AI models into Edge platforms, ensuring low

latency inference and high reliability.

Contribute to documentation, governance, and best practices for deployment,

monitoring, and lifecycle management of AI solutions in industrial ecosystems.

AI Evaluation

Conduct comprehensive evaluations of models including robustness, latency,

explainability, fairness, reliability, and operational safety in industrial settings.

Develop benchmark datasets (including IoT/industrial datasets), evaluation

frameworks, and automated testing pipelines for consistent model validation.

Analyze model architectures, industrial data characteristics, and inference

workflows to optimize performance in resource-constrained edge environments.

Partner with engineering and domain teams to align evaluation metrics with

industrial standards, validation processes, and deployment guardrails.

(External) English Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a

related quantitative discipline (or equivalent experience).

Proven experience in developing, validating, and deploying machine learning

models in production or industrial/pre-production environments.

Strong proficiency in Python with hands-on experience in data engineering, ML

experimentation, and analytics workflows.

Strong understanding of experimental design, ensemble learning

(bagging/boosting), statistical analysis, time-series modeling, and forecasting using

lag features.

Expertise in Microsoft Azure ecosystem: Databricks, Blob Storage, AI Foundry,

Container Registry, Azure Functions, and Web Services.

Hands-on experience with Computer Vision systems, Edge AI deployment, and real

time inference optimization on industrial hardware.

Experience with containerization and CI/CD tools: Docker, Git, GitHub.

Knowledge of FastAPI, Flask, Streamlit, or Gradio for building AI-enabled

applications and dashboards.

Strong foundation in NLP, Time Series Forecasting, Feature Engineering, and

Predictive Modeling.

Experience with data processing tools: Pandas, NumPy, PySpark; and visualization

tools such as Matplotlib, Power BI, and Plotly.

Strong written and verbal communication skills with the ability to explain complex

technical concepts to cross-functional teams.

Experience with LLM/SLM deployment: safetensors, Llama.cpp, ONNX Runtime,

Azure OpenAI, RAG pipelines, and prompt engineering.

Strong proficiency in AI/ML frameworks: TensorFlow/Keras, PyTorch, Scikit-learn,

LangChain, ONNX, Vector Databases, LangGraph.

Preferred Qualifications

Hands-on experience implementing AI evaluation techniques such as grounding

validation, explainability methods, and model risk assessment.

Bring your data science expertise to a team that's ready to support your growth - apply today!

Local Benefits (English):

Rewards designed for you

Our Total Rewards is our way of saying: We see you and we value you. It’s more than just pay and benefits - it’s a meaningful investment in you. It is designed to help you perform, grow, feel safe, and elevate your potential. The package helps you care for yourself and your family, plan your future, grow your skills and career, collaborate in an inclusive workplace, and contribute to your community. At Schneider Electric, we’re here for what matters most to you. Discover more at our Career Page.

Country-specific programs and initiatives may be available.

(External) English Company Boiler Plate:

Looking to make an IMPACT with your career?

When you are thinking about joining a new team, culture matters. At Schneider Electric, our values and behaviors are the foundation for creating a great culture to support business success. We believe that our IMPACT values – Inclusion, Mastery, Purpose, Action, Curiosity, Teamwork – starts with us.

IMPACT is also your invitation to join Schneider Electric where you can contribute to turning sustainability ambition into actions, no matter what role you play. It is a call to connect your career with the ambition of achieving a more resilient, efficient, and sustainable world.

We are looking for IMPACT Makers; exceptional people who turn sustainability ambitions into actions at the intersection of automation, electrification, and digitization. We celebrate IMPACT Makers and believe everyone has the potential to be one.

Become an IMPACT Maker with Schneider Electric – apply today!

€40 billion global revenue

+9% organic growth

150 000+ employees in 100+ countries

You must submit an online application to be considered for any position with us. This position will be posted until filled.

Schneider Electric aspires to be the most inclusive and caring company in the world, by providing equitable opportunities to everyone, everywhere, and ensuring all employees feel uniquely valued and safe to contribute their best. We mirror the diversity of the communities in which we operate, and ‘inclusion’ is one of our core values. We believe our differences make us stronger as a company and as individuals and we are committed to championing inclusivity in everything we do.

At Schneider Electric, we uphold the highest standards of ethics and compliance, and we believe that trust is a foundational value. Our Trust Charter is our Code of Conduct and demonstrates our commitment to ethics, safety, sustainability, quality and cybersecurity, underpinning every aspect of our business and our willingness to behave and respond respectfully and in good faith to all our stakeholders. You can find out more about our Trust Charter here

Questions about this role

Click "Apply with AI Applyd" above. We auto-fill the application from your resume and answer screening questions in seconds. No copy and paste, no juggling tabs.

Compensation for Data Scientist roles in India varies widely by seniority, employer size, and remote vs onsite arrangement. Check the salary range on this listing when published, or browse our Data Scientist hub for India medians across recent openings.

Most applications complete in under 90 seconds. You can track the status in your dashboard and watch the screenshot proof land the moment the application submits.

AI Applyd supports Greenhouse, Lever, Ashby, Workday, iCIMS, SmartRecruiters, LinkedIn Easy Apply, and most other ATS platforms. If we can submit through the platform, we do.

Want AI Applyd to auto-apply to roles like this?

We tailor your resume per posting, fill the forms, and track replies for you.