Data Scientist Job at Jash Data Sciences (Pune)

Job Description

We are seeking a versatile and proactive Data Scientist to join our dynamic team. The ideal candidate will possess a blend of technical expertise in modern AI/ML technologies, strategic planning, and effective communication skills. This role demands critical thinking, applying data science and problem-solving skills to a wide variety of real-world problems, adaptability to rapidly evolving technologies, and a strong foundation in both traditional and generative AI principles.

Job Responsibility

Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems
Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques
Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions
Build and deploy production-ready LLM applications using modern frameworks and best practices
Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models
Perform prompt engineering and optimization to maximize LLM performance for specific use cases
Implement agentic AI systems and multi-agent workflows for complex automation tasks
Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks
Build sophisticated data pipelines for large-scale data processing using modern orchestration tools
Optimize database performance and create efficient SQL queries
Deploy and monitor ML models in production using MLOps practices and containerization
Practice active listening to understand project requirements and team inputs
Collaborate with clients to translate business requirements into data science solutions
Communicate complex ideas and results clearly to stakeholders through both verbal and written formats
Apply responsible AI principles and ensure ethical considerations in model development
Demonstrate punctuality and a strong sense of ownership in all tasks
Plan strategically and multitask efficiently to meet project deadlines
Employ critical thinking to break down problems and debug effectively
Take initiative and be biased towards action to drive project progress

Requirements

Strong Python programming skills with hands-on project experience
Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods)
Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas
Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning
Experience with NLP, Computer Vision, or Time Series Analysis
Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models)
Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy)
Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS)
Strong prompt engineering skills and understanding of prompt optimization techniques
Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them
Understanding of LLM evaluation metrics and benchmarking methodologies
Familiarity with agentic AI architectures and multi-agent systems
Experience with MLOps practices and tools (MLflow, Kubeflow, Weights & Biases)
Proficiency with containerization using Docker and orchestration with Kubernetes
Experience with cloud platforms (AWS, Azure, or GCP) for ML model deployment and monitoring
Understanding of CI/CD pipelines for ML applications
Knowledge of model serving frameworks and API development (FastAPI, Flask, or Django)
Solid understanding of SQL, including advanced concepts like windowing functions and query optimization
Experience with data pipeline orchestration tools (Airflow, Prefect, or similar)
Familiarity with both SQL and NoSQL databases
Strong critical thinking and problem-solving skills
Excellent written and verbal communication abilities
Demonstrated ability to work well in a team and independently
High degree of flexibility and adaptability to rapidly evolving technologies
Understanding of AI safety principles and responsible AI practices
Data Scientist I: 0-2 years of hands-on experience in Data Science projects
Data Scientist II: 2-5 years of hands-on experience in Data Science projects
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or related technical field
Demonstrated commitment to continuous learning through courses, certifications, or self-study (especially in GenAI and modern ML techniques)

Nice to have

Experience with big data technologies (Spark, Hadoop, Databricks)
Familiarity with BI tools and dashboard creation (Tableau, Power BI, Looker)
Knowledge of graph databases and knowledge graph construction
Experience with real-time streaming data processing
Active participation in data science competitions (Kaggle, DrivenData)
Contributions to open-source AI/ML projects or technical blog
Experience with multimodal AI models (vision-language models, audio processing)
Published research papers or conference presentations

What we offer

Competitive salary commensurate with experience
Opportunity to work on diverse, cutting-edge AI/ML projects
Collaborative and innovation-driven work environment
Rapid growth and continuous learning opportunities
Exposure to latest AI technologies and industry best practices

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