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, 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).
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 careers@appfabs.in