Associate Vice President - Decision Intelligence (Data Science, AI)

RESPONSIBILITIES:

• Build, review and implement solutions with AI/GenAI, ML and deep learning (NLP) techniques and develop APIs using Python
• Able to handle large data volumes using most latest techniques and data tools
• Strong experience of working with advanced GenAI models like GPT 4, GPT 4o, Llama etc, in addition to proven expertise on AI architecture and solutions leveraging vector DBs / RAG based approaches
• Work on buy /sell-side due diligence engagements; with a strong understanding of sector and functions to be able to identify value creation opportunities for analytics application
• Hands on deliver and manage mid to large size deals and ensure smooth delivery on assigned engagements, products with regions
• Ability to communicate effectively with cross functional teams across regions and coordinate b/w the core functional and technology teams
• Stakeholder management and experience of leading mid market deals from analytics point
• Preparation of demo tools to a standard that can be shared directly with clients
• Direct client engagement both on pre-sales activities, competitive pursuit / presentation situations and client engagement delivery.
• Review of technical work of junior colleagues
• Coaching and development of junior colleagues
• A strong work initiative, high-energy level, and ability to adapt to new challenges and concepts, including a proactive approach and capacity to perform multiple workstreams and tasks
• A desire and ability to travel while working within the transaction advisory, financial accounting advisory and mergers and acquisition-oriented environment
• Experience of assisting clients with building business cases and identifying value using data-driven approaches and business intelligence
• Ability to work both independently and as part of a team, including robust communication skills
• Utilizing statistical tools to interpret data sets to identify trends and patterns
• Strong financial, accounting, analytical and communication skills, facilitating clear and concise messaging to teammates, clients and other technology personnel
• Advise stakeholders on relevant technical issues for their business area
• Uphold the firms code of ethics and business conduct.

REQUIREMENTS:

• Minimum of 8-12 years related work experience in developing and implementing AI/GenAI, ML models across industries.
• 3 years of proven experience working with natural language generation / processing, LLM techniques. Familiarity with AI/ML frameworks
• 4 years of experience in MS Azure based deployment with foundational knowledge of Azure Cognitive Services is required
• Very strong experience in application of statistical techniques like linear and non-linear regressions / classification and optimization areas as well as implementing forecasting models.
• Good to have experience on Agentic AI frameworks and workflow orchestration
• Strong experience in Merger & Acquisition domain areas like due diligence, deal structuring, financial reporting, value creation and post-merger phases
• A Bachelor s degree in Engineering from tier 1 college (Master s in Business / domain would be nice to have)
• Experienced in programming, business intelligence (BI) and enterprise resource systems, including data collection, analysis and presentation:
• Programming languages (Python must to have )
• Analytics and data Platforms (AWS, Azure, Snowflake any one or more of these, preferred Azure )
• Businesss Intelligence layer (PowerBI, Tableau etc good to have )
• Superior analytical and problem-solving skills
• Excellent interpersonal and client relationships skills
• Strong written and verbal communication skills
• Dedication to teamwork
• Proficiency in Microsoft Office, with focus on Word and Excel
• Ability to adapt to ever changing client demands
• Flexibility to travel, as needed
• Supervisory experience, willingness to mentor team members and contribute towards scaling up the practice.

TECHNICAL Requirements:

• Should have understanding on one more industry / sectors and associated KPIs from a transaction lens; across the entire deal life cycle
• Analyzing cyclicality of target s business and working capital trends
• Analyzing quality of earnings and non-recurring items
• Able to run business performance management techniques including financial reporting, scenario and optimization models
• Participating in discussions held with Management to determine data analytics, AI needs, data requests and potential impacts on the buy-side/sell-side diligence process, as well as prospective on-going projects