Responsibilities:

- Collaborate with cross-functional teams to translate business requirements into actual implementation of models, algorithms, and technologies.

- Execute the product road map and planning of the programs and initiatives as defined by the product owners.

- Independently solve complex business problems with minimal supervision, while escalating more complex issues to appropriate next level.

- Develop and maintain software programs, algorithms, dashboards, information tools, and queries to clean, model, integrate and evaluate data sets.

- Build and optimize pipelines for data intake, validation, and mining as well as modelling and visualization by applying best practices to the engineering of large data sets.

- Develop and implement advanced machine learning algorithms and models for various applications.

- Apply the latest advances in deep learning, machine learning and natural language processing to improve performance of legacy models.

- Customize latest available large language models to develop generative AI solutions for multiple business problems across multiple functional areas.

- Apply A/B testing framework and test model quality.

- Experience in taking the models to Production using Cloud Technologies

- Provide findings and analysis to take informed business decisions.

- Stay updated with the latest developments in AI/ML technologies and contribute to the continuous improvement of our systems.

Requirement:





- Minimum of 3-7 years of relevant work experience.

- Master's degree in a related field (Statistics, Mathematics or Computer Science) or MBA in Data Science/AI/Analytics

- Experience with database systems such as MySQL, PostgreSQL, or MongoDB.

- Experience in collecting and manipulating structured and unstructured data from multiple data systems (on-premises, cloud-based data sources, APIs, etc)

- Familiarity with version control systems, preferably Git.

- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.

- Solid understanding of data structures, algorithms, and distributed computing.

- Excellent knowledge of Jupyter Notebooks for experimentation and prototyping.

- Strong programming skills in Python.

- In-depth understanding of machine learning, deep learning & natural language processing (NLP) algorithms.

- Experience with popular machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.

- Knowledge of containerization tools such as Docker.

- Experience in deploying machine learning models in production environments.

- Excellent problem-solving and communication skills.

- Proficient in using data visualization tools such as Tableau or Matplotlib, or dashboarding packages like Flask, Streamlit.

- Positive working knowledge of MS PowerPoint and storyboarding skills to translate mathematical results to business insights.

📌 AI/ML (Delhi)
🏢 Deloitte Shared Services India
📍 Delhi