Associate Vice President

Job Description

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 (Pythonmust to have)
- Analytics and data Platforms (AWS, Azure, Snowflakeany one or more of these, preferred Azure)
- Businesss Intelligence layer (PowerBI, Tableau etcgood 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