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 large-scale 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 :
< 2yrs industrial experience
Mandatory/requires Skills :
Core Technical Skills (Traditional Modern AI)
Machine Learning & Statistical Analysis
Classical ML (regression classification clustering time-series)
Ensemble methods boosting decision trees
Deep Learning
CNNs for image analysis RNNs/LSTMs/Transformers for sequence/time-series data
Frameworks: TensorFlow PyTorch
Programming Languages
Python (must-have) plus SQL
Familiarity with R or MATLAB is a plus in engineering contexts
Data Engineering
Handling large-scale 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. GPT-4 Claude LLaMA) and frameworks like LangChain or Haystack
Fine-tuning or prompt engineering for domain-specific 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 multi-step reasoning and action (e.g. Auto-GPT BabyAGI CrewAI)
Chaining models and tools to solve engineering workflows (diagnosis optimization scheduling)
Using tools like LangGraph ReAct and OpenAI function-calling or tool-use APIs
AI Tool Integration
Building AI-powered tools (e.g. chatbots for field engineers document QA systems)
Leveraging vector databases (e.g. FAISS Pinecone) for retrieval-augmented generation (RAG)
Preferred Skills :
Sensor & IoT Data Analysis
Real-time 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 (scikit-learn XGBoost TensorFlow PyTorch).
Solid understanding of statistical modeling data mining and
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
