Technical Architect/Lead (Artificial Intelligence)

You will be responsible for consulting with the client to understand their AI/ML and analytics needs, as well as delivering AI/ML applications to the client. Your main tasks will include working closely with internal Business Units (BUs) and business partners (clients) to understand their business problems, designing intelligent data science solutions, identifying relevant data, developing statistical machine learning models and AI models, collaborating with the business intelligence team to build BI systems and visualizations, and working with the application team to deliver AI/ML solutions as modular offerings.

Key Responsibilities:

• Design intelligent data science solutions that deliver incremental value to end stakeholders.
• Identify relevant data and preprocess it to suitable models with the data engineering team.
• Develop statistical machine learning models, AI models using suitable tools and frameworks.
• Collaborate with the business intelligence team to build BI systems and visualizations.
• Work with the application team to deliver AI/ML solutions as modular offerings.

Qualifications Required:

• Masters/Bachelors in Computer Science, Statistics, or Economics.
• At least 6 years of experience in the Data Science field.
• Deep understanding of Machine Learning models and algorithms.
• Experience in analyzing complex business problems and translating them into data science problems.
• Understanding and experience in various Machine Learning algorithms such as Regression, Time Series, Logistic Regression, Naive Bayes, kNN, SVM, Decision Trees, Random Forest, k-Means Clustering, NLP, Text Mining, LLM (GPTs), Deep Learning, Reinforcement learning algorithm.
• Experience in machine learning frameworks like TensorFlow, Caffe, Torch, and building machine learning models using various Python packages.
• Knowledge and experience in SQL, Relational Databases, NoSQL Databases, Datawarehouse concepts.
• Understanding of AWS/Azure Cloud architecture and deployment architectures of AI/ML models (Flask, Azure function, AWS lambda).
• Knowledge of BI and visualization tools such as Tableau, PowerBI, Qlik, Plotly is an add-on.

- Soft skills required include being a good team player with excellent communication and presentation skills, proactive problem-solving abilities, and leadership qualities to manage and nurture a team of data scientists.,