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 Data Scientist (Senior Manager)
A Data Scientist in this team plays a critical role in transforming operational data into meaningful intelligence that drives better product decisions, improves workflow efficiency, and strengthens overall business outcomes. This role requires someone who can make sense of messy, high-volume datasets that come from Trust & Safety workflows, customer service patterns, issue resolution funnels, and product operations. You'll design analytical frameworks that uncover root causes, identify behavioral patterns, and reveal opportunities that are not immediately obvious from surface-level metrics. Your work will shape how teams understand performance, risk, and user experience across multiple lines of business. You will collaborate closely with product managers, engineers, operations teams, and senior leadership to design models, validate hypotheses, and translate analytical findings into clear recommendations. More importantly, you will help build a disciplined, data-driven culture by creating insights that influence strategy, guide experimentation, and support long-term transformation efforts.
Responsibilities
.Analyze large datasets from operations, workflow tools, reviewer behavior, and product surfaces to identify patterns, trends, anomalies, and root causes across different LOBs.
.Build statistical models, prediction frameworks, or pattern-recognition solutions that support content integrity, customer experience, or operational optimization initiatives.
.Design and run experiments, A/B tests, and pilots to validate hypotheses and quantify the impact of new products, policies, or workflow changes.
.Create dashboards, metric frameworks, and reporting systems that provide clear visibility into performance, quality, volume trends, and risk indicators.
.Partner with product managers, engineering teams, and operational leaders to convert analytical insights into product or process improvements.
.Conduct deep dives to understand user journeys, escalation drivers, quality breakdowns, reviewer inconsistencies, or systemic inefficiencies.
.Build segmentation models that unpack user behavior, fraud characteristics, agent decisions, or cohort-level performance trends.
.Provide data-driven risk assessments and opportunity sizing that help prioritize roadmap decisions and operational investments.
.Evaluate model performance, identify bias patterns, and recommend improvements to strengthen reliability and fairness.
.Lead structured storytelling sessions with senior stakeholders to communicate insights clearly and influence decision-making.
.Automate analytical workflows, enhance data pipelines, and ensure data integrity for recurring or large-scale analysis.

.Mentor analysts on statistical thinking, experimentation discipline, and data interpretation best practices.

Qualifications we seek in you!
Minimum Qualifications / Skills
. Post Graduation / MBA
Preferred Qualifications/ Skills
.Strong proficiency in analytical tools and languages such as Python, SQL, R, or similar environments used for statistical modeling and data exploration.
.Experience with machine learning methods including classification, clustering, regression, time-series analysis, anomaly detection, and model evaluation.
.Familiarity with Trust & Safety or Customer Service data patterns such as reviewer decisions, case metadata, escalation themes, fraud signals, or CX funnels.
.Experience working with data visualization tools and dashboards (Tableau, Looker, Power BI, or equivalent).
.Ability to translate ambiguous analytical problems into structured approaches with clear hypotheses, methods, and measurable outcomes.
.Knowledge of experimentation frameworks including A/B testing, sampling methods, significance testing, and causal inference approaches.
.Strong understanding of data pipelines, ETL workflows, and data-quality validation for large operational datasets.
.Comfort working with unstructured data, text datasets, or annotation-level information using techniques such as NLP or vectorization.
.Strong communication and storytelling skills with the ability to explain complex analytical findings to non-technical stakeholders.
.Experience collaborating with product, engineering, and operations teams to guide design decisions using data insights.
.Familiarity with cloud data environments (GCP, AWS, Azure) and distributed processing systems is a plus.
.Bachelor's degree required advanced degree in Data Science, Statistics, Computer Science, Economics, or related fields preferred.

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.