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 As a SVP/VP, you would also be required to provide expert reviews and thought leadership on your areas of specializing including helping mentor, build and scale the team Ability to communicate effectively with cross functional teams across regions and act as techno-functional bridge to coordinate b/w the core functional and technology teams Go to Market / Stakeholder management and experience of leading mid market deals from analytics point Preparation of pursuit materials, demo tools etc 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 firm's code of ethics and business conduct.
Minimum of 12-16 years related work experience in developing and implementing AI/GenAI, ML models across industries. 4 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.
Should have in depth 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