Business Analytics Lead Analyst

Job description

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 strong 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.