Executive Vice President - Business Intelligence

About TresVista

TresVista is a global enterprise offering a diversified portfolio of services that enables its clients to achieve resource optimization through leveraging an offshore capacity model. TresVista's services include investment diligence, industry research, valuation, fund administration, accounting, and data analytics. TresVista has more than 1,800 employees across offices in North America, Europe and Asia, providing high-caliber support and operating leverage to over 1,000 clients across geographies and asset classes, including asset managers, advisors, corporates and entrepreneurs.

Overview

This role shall strategize, implement, and monitor data analysis technology to improve productivity, operational efficiency, and deliver insights. You will be expected to drive adoption of Business Intelligence tools within the organization. In this role, you would drive the roadmap and strategic business objectives for the Business Intelligence division. The role shall also oversee organization automation and AI initiatives. You shall balance the risks presented by Generative AI and Predictive AI, help define our technical architecture and ensure effective execution through prioritization and governance, and build an industry leading team through recruitment, training, and development.

Roles and Responsibilities

• Building Data Lake:

a. Architecting enterprise data lake

b. Evaluating and finalizing tech stack for data lake

c. Leading initiatives to deliver data lake

d. Designing and implementing data governance framework

• Developing data visualization:

a. Understanding decisioning situation and map it to analytics needs

b. Defining, designing, and conceptualizing projects of data visualization

c. Ensuring the overall user experience is considered when designing deploying innovative solutions and services

• Leveraging Advance Analytics and AI:

a. Identifying opportunities of leveraging predictive technology to automate decisions

b. Driving initiatives around generative AI applications, exploring new use cases like content automation, conversational interfaces, and dynamic product features

c. Designing, developing, and deploying AI including NLP models for tasks such as text classification, sentiment analysis, machine translation, and question answering

• Project Implementation and management:

a. Presenting project and securing approvals

b. Launching project, executing then, and doing project management for Business Intelligence vertical

c. Recording product defects, analyzing requirements and work on impact analysis of planned features

d. Gathering Product Data including user behavior, web analytics, product usage, KPIs/KRA for feature(s) and synthesizing insights

Prerequisites

• Strong understanding of data science concepts, machine learning, and advanced analytics
• Experience in managing technical teams to deliver Data solutions, incl. acquisition, curation, catalogue registration, data product life cycle and data producer and consumer journeys and usage patterns
• Experienced with planning, estimating, organizing, and delivering on multiple projects ▪ Ability to articulate solutions and process designs clearly
• Strong knowledge of data integration (ETL), data quality (DQ), data governance, iPaaS (APIs, micro services, application Integration) and Big Data
• Good web development background (SQL, RDBMS, Java, HTML5, NET) is a plus
• Good understanding of Machine Learning tools and its usage such as Python/R

Experience

• Candidate should have at least 12 - 18 years of hands-on experience in data science, analytics and machine learning with at least 5+ years in a leadership role
• Excellent leadership, communication and collaboration skills with a proven ability to align AI initiatives with business goals and deliver measurable outcomes
• Strategic thinking, problem-solving and a strong team player

Education

• A bachelor/master's degree from a Tier I institute or a Ph.D. in data science, computer science, statistics, mathematics, machine learning or a related quantitative field is preferred

Compensation

• The compensation structure will be as per industry standards