Jr Data Scientist (AI/ML)
Jr Data Scientist (AI/ML)
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Job Description
Roles & Responsibilities :
Design and develop scalable machine learning models for predictive analytics classification and optimization tasks.
Work closely with data engineering teams to gather clean and transform largescale data for model training and evaluation.
Conduct A/B testing and performance monitoring of deployed models.
Communicate complex model outcomes and business impact to stakeholders in a clear and concise manner.
Contribute to model lifecycle management including retraining pipelines and MLOps best practices.
Qualifications :
Educational qualification:
Masters or PhD in Computer Science Data Science Mathematics or related field.
BE/BTECH in computer Science
Experience :
4 industrial experience
Mandatory/requires Skills :
Core Technical Skills (Traditional Modern AI)
Machine Learning & Statistical Analysis
Classical ML (regression classification clustering timeseries)
Ensemble methods boosting decision trees
Deep Learning
CNNs for image analysis RNNs/LSTMs/Transformers for sequence/timeseries data
Frameworks: TensorFlow PyTorch
Programming Languages
Python (musthave) plus SQL
Familiarity with R or MATLAB is a plus in engineering contexts
Data Engineering
Handling largescale data ETL pipeline design
Tools: Spark Airflow dbt etc.
Visualization & Reporting
Python (Seaborn Plotly) Tableau Power BI
AI / GenAI / Agentic AI Skills
Generative AI (GenAI)
Experience with LLMs (e.g. GPT4 Claude LLaMA) and frameworks like LangChain or Haystack
Finetuning or prompt engineering for domainspecific tasks (e.g. maintenance logs technical documents)
Use of GenAI for report generation document summarization and automated insights
Agentic AI Systems
Designing autonomous agents capable of multistep reasoning and action (e.g. AutoGPT BabyAGI CrewAI)
Chaining models and tools to solve engineering workflows (diagnosis optimization scheduling)
Using tools like LangGraph ReAct and OpenAI functioncalling or tooluse APIs
AI Tool Integration
Building AIpowered tools (e.g. chatbots for field engineers document QA systems)
Leveraging vector databases (e.g. FAISS Pinecone) for retrievalaugmented generation (RAG)
Preferred Skills :
Sensor & IoT Data Analysis
Realtime data processing anomaly detection predictive maintenance
Simulation & Modeling
Integration with engineering simulation data digital twins
Optimization & Control
Operations research control systems system dynamics reinforcement learning for control tasks
Additional Information :
Requirements:
Strong programming skills in Python R or Scala with proficiency in ML libraries (scikitlearn XGBoost TensorFlow PyTorch).
Solid understanding of statistical modeling data mining and
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
