Senior data analyst

We are looking for a versatile and highly skilled Data Analyst / AI Engineer (Immediate Joiner) to join our innovative team. This unique role combines the strengths of a data scientist with the capabilities of an AI engineer, allowing you to dive deep into data, extract meaningful insights, and then build and deploy cutting-edge Machine Learning, Deep Learning, and Generative AI models. You will play a crucial role 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, Num Py, 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 Tensor Flow, Keras, or Py Torch.- Experience with CNNs (Convolutional Neural Networks) and computer vision concepts (e.g., Open CV, 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 Lang Chain or Llama Index.- 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 Sage Maker, 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).Educational Qualification:- Bachelor’s degree in Computer Science, Information Technology, or a related field (or equivalent experience).Those who are interested please share your resume to