Senior Data Scientist

We are seeking a highly skilled and results-oriented Senior Data Scientist with over three years of professional experience in data science, machine learning, artificial intelligence, and predictive analytics. The ideal candidate will possess strong expertise in Python, machine learning frameworks, statistical modeling, and AI-powered tools, with a proven ability to transform complex datasets into actionable business insights. This role involves developing, training, evaluating, and deploying machine learning models while leveraging modern AI tools and frameworks to create scalable, data-driven solutions. Experience with Generative AI, Large Language Models (LLMs), and cloud-based AI services will be a significant advantage.

Key Responsibilities

- Collect, clean, process, and analyze both structured and unstructured datasets to uncover patterns, trends, and business opportunities.
- Develop, train, evaluate, and optimize machine learning and deep learning models for practical applications.
- Build predictive models, classification and regression systems, recommendation engines, and forecasting solutions.
- Utilize Python libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, and Seaborn for data analysis, visualization, and model development.
- Work extensively with machine learning and deep learning frameworks including TensorFlow, PyTorch, and Keras.
- Leverage AI tools, Generative AI, LLMs, and prompt engineering techniques to develop intelligent applications and automate workflows.
- Apply statistical analysis, hypothesis testing, feature engineering, and model validation methods to enhance model performance.
- Develop data pipelines and integrate machine learning models into production environments through APIs and backend services.
- Collaborate closely with software engineers, data engineers, product managers, and business stakeholders to deliver AI-driven solutions.
- Monitor deployed models, assess performance, detect data drift, and implement necessary improvements.
- Document technical processes, model architectures, experiments, and analytical findings clearly and comprehensively.
- Stay current with emerging AI technologies, machine learning methodologies, and industry best practices.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related discipline.
- Strong proficiency in Python and key libraries including Pandas, NumPy, and Scikit-learn.
- Hands-on experience with machine learning and deep learning frameworks such as TensorFlow or PyTorch.
- Knowledge of Generative AI, Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), and AI tools/frameworks like LangChain, LlamaIndex, or Hugging Face.
- Solid understanding of statistics, data analysis, feature engineering, and model evaluation techniques.
- Experience with SQL, data visualization tools, and REST API development using FastAPI or Flask.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP), containerization tools like Docker, version control with Git, and MLOps tools such as MLflow.
- Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

- Practical experience with Generative AI, LLMs, RAG, embeddings, and vector databases.
- Familiarity with AI frameworks and tools including LangChain, LlamaIndex, Hugging Face, OpenAI APIs, or similar technologies.
- Exposure to cloud platforms like AWS, Microsoft Azure, or Google Cloud Platform.
- Knowledge of MLOps best practices including model monitoring, CI/CD pipelines, and experiment tracking tools such as MLflow.
- Experience working with large datasets and data engineering pipelines.
- Background in natural language processing (NLP), computer vision, recommendation systems, or time-series forecasting.

This position offers the opportunity to work at the forefront of AI and machine learning, contributing to impactful projects that drive business innovation and efficiency.