Assistant Vice President

EXL Decision Analytics

EXL (NASDAQ:EXLS) is a leading operations management and analytics company that helps businesses enhance growth and profitability in the face of relentless competition and continuous disruption. Using our proprietary, award-winning Business EXLerator Framework™, which integrates analytics, automation, benchmarking, BPO, consulting, industry best practices and technology platforms, we look deeper to help companies improve global operations, enhance data-driven insights, increase customer satisfaction, and manage risk and compliance. EXL serves the insurance, healthcare, banking and financial services, utilities, travel, transportation, and logistics industries. Headquartered in New York, New York, EXL has more than 51,000 professionals in locations throughout the United States, Europe, Asia (primarily India and Philippines), Latin America, Australia, and South Africa.

EXL Analytics provides data-driven, action-oriented solutions to business problems through statistical data mining, cutting edge analytics techniques and a consultative approach. Leveraging proprietary methodology and best-of-breed technology, EXL Analytics takes an industry-specific approach to transform our clients’ decision making and embed analytics more deeply into their business processes. Our global footprint of nearly 2,000 data scientists and analysts assist client organizations with complex risk minimization methods, advanced marketing, pricing and CRM strategies, internal cost analysis, and cost and resource optimization within the organization. EXL Analytics serves the insurance, healthcare, banking, capital markets, utilities, retail and e-commerce, travel, transportation, and logistics industries.

Please visit www.exlservice.com for more information about EXL Analytics.

Roles and Responsibilities for Senior Business Analyst- GenAI

• Business Requirement Analysis: Gather, analyze, and document business requirements related to Generative AI solutions, ensuring alignment with business goals and objectives.
• AI Solution Design: Work closely with technical teams to define and design AI-powered solutions that meet business needs, leveraging Generative AI technologies such as GPT, GANs, and NLP models.
• Stakeholder Engagement: Collaborate with key stakeholders, including product managers, data scientists, and business leaders, to understand business challenges and identify opportunities for AI-driven transformation.
• Product Strategy Alignment: Define and communicate product strategies for GenAI applications, ensuring that AI solutions are effectively integrated into business processes and systems.
• Data & Process Analysis: Conduct thorough analysis of existing data and processes to identify areas where GenAI can drive efficiency, innovation, and value.
• AI Performance Monitoring: Track the performance and impact of GenAI solutions, using key metrics to evaluate success and identify areas for optimization.
• Market Research & Trend Analysis: Stay updated on the latest trends and advancements in Generative AI, and conduct market research to identify new opportunities for AI adoption within the organization.
• Risk Management: Identify potential risks related to the implementation of GenAI technologies, including ethical concerns, bias, and data privacy issues, and work with teams to mitigate them.
• Documentation and Reporting: Produce clear documentation, including business requirements, use cases, and process flows, and report on the progress and outcomes of GenAI initiatives to senior leadership.
• Cross-Functional Collaboration: Work closely with data scientists, AI engineers, and IT teams to ensure that GenAI solutions are delivered on time and meet business requirements.
• Change Management: Support change management activities related to GenAI implementations, including training, communication, and adoption across the organization.
• Continuous Improvement: Provide feedback and recommendations for continuous improvement of GenAI processes, models, and solutions based on business feedback and performance analysis.

Candidate Profile:

• Experience: 5+ years of experience as a Business Analyst in the Asset Management industry, with a strong focus on leveraging Generative AI technologies to drive business transformation and innovation.
• Asset Management Knowledge: Deep understanding of asset management processes, including portfolio management, risk management, financial modeling, and investment strategies, with the ability to integrate AI solutions into these areas.
• Generative AI Expertise: Familiarity with Generative AI models (e.g., GPT, GANs, NLP) and their applications within financial services and asset management, including automation, risk analysis, and predictive modeling.
• Stakeholder Management: Proven ability to engage with and manage diverse stakeholders (including portfolio managers, traders, data scientists, and senior leadership) to align GenAI solutions with strategic business objectives.
• Business Process & Data Analysis: Expertise in analyzing business processes and data flows within asset management operations, identifying areas for improvement, and recommending AI-driven solutions for process automation, efficiency, and decision-making.
• Financial Analytics: Strong background in financial data analysis, understanding how AI can enhance data-driven insights for portfolio optimization, trading strategies, and performance reporting.
• Project Management: Experience in managing AI implementation projects in an agile environment, collaborating across teams to deliver high-impact AI solutions on time and within budget.
• Communication Skills: Excellent communication skills, with the ability to explain complex Generative AI concepts to non-technical stakeholders, and articulate business value, particularly in the context of asset management.
• AI Ethics & Compliance: Knowledge of ethical considerations in AI, particularly in asset management, including bias mitigation, regulatory compliance, and data privacy concerns.
• Problem Solving & Innovation: Strong problem-solving and critical thinking skills to creatively apply GenAI solutions to real-world challenges in asset management, such as market forecasting, risk modeling, and client reporting.
• Market Awareness: Awareness of the latest trends in Generative AI and their impact on the asset management industry, including AI-driven investment strategies, automated trading, and client insights.
• Collaboration: Ability to collaborate with cross-functional teams, including data scientists, quants, portfolio managers, and business leaders, to drive AI projects that align with business goals and regulatory standards.
• Education: A degree in Finance, Business Administration, Computer Science, Data Science, or a related field. Advanced qualifications or certifications in AI, machine learning, or asset management are a plus.

What we offer:

• EXL Analytics offers an exciting, fast paced, and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world-class analytics consultants.
• You can expect to learn several aspects of businesses that our clients engage in. You will also learn effective teamwork and time-management skills - key aspects for personal and professional growth. 
• Analytics requires different skill sets at various levels within the organization. At EXL Analytics, we invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques.
• We provide guidance/ coaching to every employee through our mentoring program wherein every junior level employee is assigned a senior level professional as advisors.
• Sky is the limit for our team members. The unique experiences gathered at EXL Analytics set the stage for further growth and development in our company and beyond.

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