Navneet Nimish
Senior Data Scientist @FIS
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WORK HISTORY
Senior Data Scientist @FIS
Bellevue, WA, US
Designed and executed randomized control trials with product & compliance partners to deliver a rule-augmented fraud engine; applied causal inference to validate AML risk models; reduced investigation turnaround by 35% across 10+ brands and 3 FIs.• Engineered and deployed XGBoost fraud risk model (70+ features) with Python APIs on AWS; enabled proactive interventions and targeted recoveries of $1.2M+ annually across high-volume ACH transactions; delivered ~85% precision and automated $2.5M+ in annual holds.• Redesigned SQL/AWS data pipelines and modernized visualization dashboards, enabling real-time KPI tracking, and improved compliance transparency.• Mentored senior and mid-level data scientists; scaled best practices in ML modeling, experimentation, and statistical analysis, raising rigor across fraud analytics portfolio.
EDUCATION
UMN Carlson School of Management
Master of Science in Business Analytics, Business Analytics
Indian Institute of Technology, Roorkee
Bachelor of Technology - BTech, Process Engineering
Indian Institute of Technology, Roorkee
Master of Business Administration - MBA, Finance, General
SKILLS
ABOUT NAVNEET NIMISH
Strategic DS leader with 10+ years of experience delivering measurable business impact through advanced analytics, ML modeling, and experimentation at scale. Proven track record of leading end-to-end product and business data science initiatives—from opportunity sizing and causal inference to scalable deployment of models in production. Adept at translating ambiguous problems into data-driven strategies, mentoring high-performing teams, and driving cross-functional alignment with product, engineering, and business partners.Expertise includes- Machine Learning: Supervised/unsupervised learning, forecasting, model monitoring- Causal Inference & Experimentation: A/B testing, uplift modeling, quasi-experiments- Analytics & Insights: Opportunity sizing, funnel analysis, retention/churn, growth attribution, customer segmentation- Business Strategy: KPI development, OKRs, product roadmap influence, operational efficiency- Tools & Technologies: Python, SQL, R, Spark, Snowflake, BigQuery, Databricks, Airflow, Tableau, Power BI, Looker- Leadership: Team building, stakeholder management, cross-functional influence, mentoring
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