Data Scientist

Job Description

We are a fast-growing startup based in Pune, India, specializing in cutting-edge Data Science and Data Engineering solutions. Our team of dedicated professionals is committed to solving complex data challenges for companies worldwide. Our Culture We foster a vibrant startup culture that values: Intellectual curiosity Continuous learning Positive work environment Collaborative problem-solving Role Overview 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. Key Responsibilities 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 Required Skills Core Programming & ML 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 Generative AI & LLMs 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 MLOps & Deployment 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) Data Engineering & Databases 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 Soft Skills & Professional Attributes 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 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 Qualifications 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) 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