Senior Data Analyst

As a versatile and highly skilled Data Analyst / AI Engineer, you will have the opportunity to combine the strengths of a data scientist and an AI engineer. Your role will involve diving deep into data, extracting meaningful insights, and building and deploying cutting-edge Machine Learning, Deep Learning, and Generative AI models. You will be instrumental in transforming raw data into strategic assets and intelligent applications. **Key Responsibilities:** - **Data Analysis & Insight Generation:** - Perform in-depth Exploratory Data Analysis (EDA) to identify trends, patterns, and anomalies in complex datasets. - Clean, transform, and prepare data from various sources for analysis and model development. - Apply statistical methods and hypothesis testing to validate findings and support data-driven decision-making. - Create compelling and interactive BI dashboards (e.g., Power BI, Tableau) to visualize data insights and communicate findings to stakeholders. - **Machine Learning & Deep Learning Model Development:** - Design, build, train, and evaluate Machine Learning models (e.g., regression, classification, clustering) to solve specific business problems. - Develop and optimize Deep Learning models, including CNNs for computer vision tasks and Transformers for Natural Language Processing (NLP). - Implement feature engineering techniques to enhance model performance. - **Generative AI Implementation:** - Explore and experiment with Large Language Models (LLMs) and other Generative AI techniques. - Implement and fine-tune LLMs for specific use cases (e.g., text generation, summarization, Q&A). - Develop and integrate Retrieval Augmented Generation (RAG) systems using vector databases and embedding models. - Apply Prompt Engineering best practices to optimize LLM interactions. - Contribute to the development of Agentic AI systems that leverage multiple tools and models. **Required Skills & Experience:** - **Data Science & Analytics:** - Strong proficiency in Python and its data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn). - Proven experience with Exploratory Data Analysis (EDA) and statistical analysis. - Hands-on experience developing BI Dashboards using tools like Power BI or Tableau. - Understanding of data warehousing and data lake concepts. - **Machine Learning:** - Solid understanding of various ML algorithms (e.g., Regression, Classification, Clustering, Tree-based models). - Experience with model evaluation, validation, and hyperparameter tuning. - **Deep Learning:** - Proficiency with Deep Learning frameworks such as TensorFlow, Keras, or PyTorch. - Experience with CNNs (Convolutional Neural Networks) and computer vision concepts (e.g., OpenCV, object detection). - Familiarity with Transformer architectures for NLP tasks. - **Generative AI:** - Practical experience with Large Language Models (LLMs). - Understanding and application of RAG (Retrieval Augmented Generation) systems. - Experience with Fine-tuning LLMs and Prompt Engineering. - Familiarity with frameworks like LangChain or LlamaIndex. - **Problem-Solving:** - Excellent analytical and problem-solving skills with a strong ability to approach complex data challenges. **Good to Have:** - Experience with cloud-based AI/ML services (e.g., Azure ML, AWS SageMaker, Google Cloud AI Platform). - Familiarity with MLOps principles and tools (e.g., MLflow, DVC, CI/CD for models). - Experience with big data technologies (e.g., Apache Spark). If you are interested in this role, please share your resume to careers@appfabs.in.,