Key Skills: AI/ML, Forecasting, SQL, Python, Budgeting, Predictive Analysis, Cloud (AWS / Azure / GCP)

Roles and Responsibilities:

Core Technical Skills

- Develop and implement solutions using Python, machine learning, and AI engineering.

- Apply GenAI, LLMs, small language models, RAG, and agentic AI to business use cases.

- Design, develop, and tune NLP and predictive models.

- Build and manage data workflows on platforms such as Databricks or similar platforms.

- Apply solid prompt engineering fundamentals to AI and GenAI solutions.

Problem-Solving and Business Skills

- Translate business needs into effective technical solutions, focusing on measurable business outcomes.

- Work with Finance datasets and ERP-related data.

- Apply curiosity, adaptability, and a problem-solving mindset to develop new solutions.

- Partner with engineering teams and AI CoEs to productize analytics and AI/ML models.

Ways of Working

- Start small, iterate quickly, and continuously improve solutions based on feedback.

- Collaborate directly with global Finance stakeholders.

- Work effectively in global environments with empathy for end users.

- Build and experiment with new AI capabilities and solutions.

- Contribute to shaping analytics and AI roadmaps and initiatives.

Skills Required:

- 5-8 years of experience in analytics, data science, or business intelligence, with at least 5 years in a leadership or lead role.





- Experience delivering analytics or automation initiatives for Finance or FP&A; functions.

- Knowledge of finance data domains such as general ledger, allocations, forecasting, and planning.

- Strong skills in Power BI, Databricks, Microsoft Fabric, and Denodo.

- Strong hands-on experience with Python, machine learning, and AI engineering.

- Experience with GenAI, LLMs, small language models, RAG, and agentic AI.

- Experience with NLP, predictive analytics, forecasting, and machine learning models.

- Familiarity with AI/ML frameworks and tools such as Python, TensorFlow, and Azure ML.

- Experience working with Finance datasets or ERP-related data.

- Experience partnering with engineering teams and AI CoEs to productize models.

- Strong communication and stakeholder management skills.

- Ability to work effectively with global Finance stakeholders and distributed teams.

- Strong problem-solving, analytical, and business-oriented mindset.

- Ability to work independently, experiment, iterate, and develop solutions in an evolving environment.

Good to Have

- Certifications such as Azure AI Engineer or Data Science Professional.

- Experience with emerging GenAI and automation tools.

- Experience building AI capabilities and analytics solutions for Finance functions.

Education: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Business Analytics, Finance, or a related field.

📌 Business Analytics Lead Analyst (Bengaluru)
🏢 Careernet
📍 Bengaluru