Data Scientist

As a Data Scientist, you will identify business trends and solve complex business problems through advanced analytics, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Generative AI, and Agentic AI solutions. You will interpret results from multiple data sources using a variety of techniques, ranging from statistical analysis and predictive modeling to large-scale AI systems. You will design, develop, and implement high-value business solutions that drive innovation, automation, and business outcomes. You will prepare and analyze large datasets, build data models, develop scalable AI solutions, and support the organization's digital transformation initiatives.

Responsibilities:

1. Work on existing Digital Products and understand, enhance, and continuously improve intelligent models and AI-driven solutions.
2. Work with stakeholders to identify opportunities from data, drive innovation, and foster a culture of invention and continuous improvement.
3. Translate data into actionable insights that empower confident decision-making, product development, business strategies, and operational optimization.
4. Research, develop, plan, and implement predictive AI/ML/DL models, Generative AI applications, Agentic AI workflows, and optimization techniques across digital products.
5. Develop, manage, and maintain Machine Learning, Deep Learning, and Large Language Model (LLM)-based solutions.
6. Assess the effectiveness, accuracy, and value of new data sources, AI technologies, and data-gathering techniques.
7. Coordinate with cross-functional teams to deploy, monitor, and improve AI solutions in production environments.
8. Develop processes and tools to monitor model performance, AI system reliability, data quality, and business impact.
9. Stay current with emerging AI technologies and proactively identify new projects and business opportunities.

Qualifications:

1. Master's Degree in Computer Science, Data Science, Artificial Intelligence, Electrical Engineering, or a related field. Ph.D. preferred.
2. Strong oral and written communication skills.
3. A collaborative mindset to excel in a team environment.
4. Ability to solve complex business problems with innovative and practical solutions.
5. Proven track record of driving innovation and delivering business value through AI and analytics.
6. Ability to manage multiple priorities and deliver effective solutions in a fast-paced environment.
7. Experience with distributed data and computing platforms such as Spark, Databricks, Hadoop, Hive, Airflow, SQL, and cloud-native technologies.
8. Strong foundation in statistics, machine learning, and data science techniques.
9. Strong Python programming expertise with experience building scalable AI/ML applications, data pipelines, APIs, and production-grade solutions. Experience with Java, C++, R, or JavaScript is a plus.
10. 3+ years of experience with deep learning frameworks such as PyTorch, TensorFlow, Keras, or equivalent.
11. Proven experience in independent research, innovation, and complex problem-solving, including publications, patents, or significant industry contributions.
12. Proven experience developing and deploying AI/ML solutions in enterprise or industrial environments.
13. 5+ years of overall experience in Data Science, Machine Learning, Artificial Intelligence, and Advanced Analytics.
14. 3+ years of experience in Generative AI, including LLMs, RAG, prompt engineering, model evaluation, fine-tuning, and AI application development.
15. 3+ years of experience in Agentic AI, AI agents, multi-agent systems, autonomous workflows, tool calling, and orchestration frameworks.
16. Experience with AI frameworks and platforms such as LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, Azure AI Foundry, and Vector Databases.
17. Good-to-have experience in UI development using React, Angular, Streamlit, Gradio, or similar technologies for building AI-powered applications and copilots.

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