Business Analyst - LDT

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose - the relentless pursuit of a world that works better for people - we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI.
Inviting applications for the role of Product Expert - AI Operations (Senior Manager)
A Product Expert / Product Manager in AI Operations plays a central role in shaping how large-scale AI and ML ecosystems operate, learn, and improve. This role demands someone who can deeply understand the products and models we support, how human-in-the-loop workflows impact model quality, and how operational data feeds into model evolution. You'll analyze annotation flows, content / data labeling quality, model failure patterns, and reviewer behavior to uncover insights that help product and engineering teams build smarter and safer AI systems. This role blends research, product thinking, and operational intelligence-you'll evaluate how policies, tooling, and workflows influence model training and inference outcomes, while identifying opportunities to improve data quality, reduce annotation friction, and enhance overall model performance. You'll partner closely with AI product managers, ML engineers, and operational stakeholders to influence roadmaps, recommend changes to labeling strategies, and drive initiatives that strengthen the reliability and scalability of AI operations. Ultimately, your work will help build AI systems that perform better, adapt faster, and deliver meaningful improvements to end users.
Responsibilities
.Lead deep-dive research into AI model workflows, human-in-the-loop review cycles, and annotation processes to identify gaps that affect model quality, precision, and recall.
.Analyze labeling patterns, ambiguity clusters, edge-case categories, and annotation disagreements to generate product-level recommendations.
.Conduct audits of annotation tools, reviewer UX, task structures, and sampling mechanisms to uncover inefficiencies and opportunities to improve data throughput.
.Work closely with AI product managers and ML engineers to improve labeling taxonomies, define annotation guidelines, and refine model training requirements.
.Identify failure patterns in model predictions, assess root causes, and translate findings into actionable recommendations for product and engineering teams.
.Lead operational experiments and pilots to validate new workflows, updated guidelines, or changes to reviewer-tooling before broader implementation.
.Convert operational reviews, metadata trends, and quality audits into insights that inform model training strategies, feature needs, and product investments.
.Partner with cross-functional stakeholders across operations, quality, training, and engineering to ensure alignment and drive adoption of AI workflow improvements.
.Build structured narratives and product briefs that articulate AI operational risks, data quality gaps, and opportunities for predictive improvement.
.Identify and advocate for automation and tooling advancements, including ML-assisted annotation, auto-labeling, clustering, and quality assurance innovations.

.Support readiness planning for model launches, updates, or policy changes, ensuring operational teams are equipped to manage new requirements.
.Mentor junior analysts on AI operations fundamentals, structured thinking, and model evaluation methodologies.

Qualifications we seek in you!
Minimum Qualifications / Skills
. Post Graduation / MBA
Preferred Qualifications/ Skills
.Strong understanding of AI operations, human-in-the-loop systems, annotation strategies, and supervised learning workflows.
.Familiarity with ML concepts including training data pipelines, ground-truth quality, feature labeling, taxonomies, keyword hierarchies, and model evaluation metrics.
.Experience working with ML/AI product, engineering, or data science teams to refine guidelines, requirements, or annotation strategies.
.Knowledge of labeling tools, annotation platforms, quality scoring frameworks, sampling methodologies, and reviewer decisioning systems.
.Strong analytical skills with experience in error analysis, confusion matrices, edge-case segmentation, and root-cause pattern identification.
.Exposure to AI/ML technologies such as classification models, ranking systems, safety models, active learning, reinforcement learning, or LLM-assisted workflows.
.Ability to conduct structured research including workflow audits, field studies, data quality assessments, and competitive landscape benchmarking.
.Proven ability to translate ambiguous operational issues into clear product problem statements and actionable recommendations.
.Strong communication and storytelling skills, with an ability to present AI-related concepts to non-technical operations and leadership teams.
.Experience managing cross-functional relationships with product, engineering, operations, training, and QA partners in fast-paced environments.
.Familiarity with tools such as Python, SQL, or analytics platforms is a plus (even if not hands-on coding).
.MBA or advanced degree preferred background in AI operations, data annotation, or ML-driven products is an advantage.

Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.
Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.