Senior Data Scientist, ML & Causal Inference Leader

Arbi Anjargholi

Staff Data Scientist, Springfield, IL 62702

LinkedIn: https://www.linkedin.com/in/datamanned/

Email: ****.*****@*****.*** Phone: +1-484-***-**** Summary

Seasoned Data Scientist with 12+ years of experience designing, deploying, and scaling machine learning, causal inference, and predictive modeling solutions across enterprise environments. Proven track record advancing data science capabilities at leading companies, including LiveRamp, Catalina, Walgreens, and IRI-delivering identity resolution systems, omnichannel personalization models, marketing measurement, and privacy-safe data pipelines operating at massive scale. Expert in developing end-to-end ML architectures, distributed data workflows, MMM and incrementality frameworks, and high-volume production models supporting billions of transactions and consumer records. A cross-functional technical leader known for blending statistical rigor with product intuition, driving measurable business impact, and elevating data science maturity across organizations. Deep experience in Python, SQL, Spark, causal inference, Bayesian modeling, uplift modeling, time series forecasting, and cloud-native ML operations. Adept at partnering with Product, Engineering, Analytics, and business stakeholders to translate complex data insights into actionable strategies. Recognized for mentoring teams, defining best practices for experimentation and model governance, and building scalable, secure, and ethically grounded AI/ML solutions. Technical Skills

Languages & Tools: Python (Pandas, NumPy, Scikit-learn, PySpark, TensorFlow, PyTorch), SQL, Spark, R, Git, Linux. Machine Learning: Predictive modeling, causal inference, uplift modeling, MMM, attribution, time series forecasting, segmentation, clustering, ensemble methods, entity resolution, anomaly detection. Data Engineering: ETL/ELT pipelines, distributed data processing, workflow orchestration (Airflow), APIs, data modeling, data quality frameworks.

Cloud & Big Data: GCP, AWS, Databricks, Snowflake, BigQuery, Redshift, Hadoop ecosystem. MLOps: Model deployment, CI/CD, automated training pipelines, monitoring, feature engineering frameworks, reproducibility.

Generative AI & LLMs: RAG, embeddings, prompt engineering, transformer models, LangChain/LlamaIndex. Analytics & Visualization: Tableau, Looker, Power BI, advanced experimentation (A/B testing, matched markets), econometrics.

Experience

LiveRamp (Chicago, IL)

Staff Data Scientist Jan 2022 - Present

Developed and productionized large-scale machine learning solutions supporting identity resolution, entity matching, and data enrichment across billions of consumer and enterprise records.

Advanced LiveRamp’s privacy-safe identity graph by architecting algorithms that improved match accuracy, coverage, and stability while adhering to strict compliance and data ethics requirements.

Designed automated data pipelines and distributed ML workflows (Python, SQL, Spark) to support high-volume, cross-cloud data collaboration use cases.

Built causal inference, attribution, and measurement frameworks enabling enterprise customers to quantify marketing effectiveness and optimize spend.

Collaborated closely with Product, Engineering, and Privacy teams to integrate ML capabilities into LiveRamp’s enterprise-grade data collaboration platform.

Led R&D on novel modeling techniques - including Bayesian methods, time-series modeling, and ensemble architectures - to enhance robustness and predictive performance.

Developed internal ML tooling for model training, evaluation, monitoring, and observability, improving deployment efficiency across teams.

Served as a technical mentor to data scientists and analysts, establishing best practices around experimentation, model governance, documentation, and reproducibility.

Led development of internal Generative AI tooling, including LLM-powered documentation assistants and model diagnostic helpers, improving productivity for data science and engineering teams.

Built RAG prototypes leveraging enterprise metadata, embeddings, and transformer-based retrieval to support privacy-safe data collaboration and internal knowledge search.

Designed and tested LLM-driven entity matching enhancements to complement traditional ML pipelines, improving explainability and candidate generation in identity resolution workflows.

Integrated prompt engineering and LLM-based evaluation methods into model governance processes to streamline reviews, automate narrative summaries, and improve cross-team communication. Catalina USA (Chicago, IL)

Senior Data Scientist Apr 2015 - Jan 2022

Designed and deployed end-to-end machine learning models for shopper targeting, personalization, and media optimization, driving measurable lift across omnichannel campaigns.

Built predictive models for shopper propensity, product affinity, churn risk, and cross-category engagement using large-scale purchase, behavioral, and demographic data.

Developed closed-loop measurement frameworks using causal inference, uplift modeling, and matched-market designs to quantify marketing incrementality.

Created AI-optimized segmentation and audience-building algorithms that powered Catalina’s managed media services portfolio.

Built scalable data pipelines and automated modeling workflows using Python, SQL, and distributed computing environments to support real-time audience activation across retail networks.

Partnered with cross-functional teams-including Product, Engineering, Analytics, Account Strategy, and Retail Partners-to translate business requirements into actionable data science solutions.

Conducted experimentation and A/B testing to evaluate media impact, pricing changes, promotional strategies, and in-store/CTV channel interactions.

Collaborated with privacy and compliance teams to ensure all modeling processes adhered to Catalina’s strict consumer data protection and ethics standards.

Provided data science leadership for key CPG and retail initiatives, delivering insights that shaped client strategies and improved campaign ROI.

Mentored analysts and data scientists, establishing best practices in feature engineering, modeling, documentation, and model governance.

IRI (Chicago, IL)

Consultant II, Strategic Analytics Nov 2014 - Apr 2015

Conducted advanced statistical and predictive analyses using large-scale retail scanner, loyalty, and causal data to generate insights on pricing, promotion, distribution, and media effectiveness.

Supported strategic initiatives for major CPG and retail clients by developing models and dashboards that quantified lift from in-store promotions, digital campaigns, and category management strategies.

Built and automated reporting frameworks providing client teams with actionable performance metrics and scenario-based decision support.

Delivered actionable recommendations that guided assortment optimization, marketing investment, and customer engagement strategies for national brands.

Collaborated with cross-functional client teams-including marketing, category management, sales, and research-to translate analytical findings into practical business initiatives.

Ensured data accuracy, quality, and alignment across multiple large datasets, improving reliability of client- facing insights.

Walgreens (Deerfield, IL)

Senior Analyst, Advanced Analytics & Pharmacy Insights Dec 2012 - Nov 2014

Designed and executed analytics to evaluate promotional events, targeted offers, and customer engagement, identifying key drivers of lift, retention, and ROI.

Delivered detailed insights supporting pharmacy marketing initiatives, patient engagement programs, and healthcare-focused strategic decisions.

Conducted deep-dive analyses on Walgreens' enterprise data-mart and large-scale customer transaction data to uncover behavior patterns, segmentation insights, and performance trends.

Prepared large-scale pharmacy data tables, dashboards, and performance metrics highlighting market conditions, prescription dynamics, and competitive signals.

Proposed and implemented more efficient data processing methods, reducing turnaround time and improving scalability of analytics workflows.

Built reusable analytical frameworks and solution sets that were adopted by cross-functional teams for ongoing reporting and decision support.

Partnered with marketing, merchandising, and pharmacy leadership to translate complex analytics into actionable recommendations aligned with Walgreens’ healthcare and retail strategy.

Designed analytics to evaluate promotional events, offers, and customer engagement, identifying drivers of lift and ROI.

Conducted deep-dive analyses using Walgreens’ data-mart and large-scale customer transaction datasets to uncover behavior patterns and performance trends.

Built reusable analytical solution sets and frameworks, enabling faster insights generation for business and analytics partners.

CAC Group, Inc. (Schaumburg, IL)

Senior Analyst Mar 2012 - Nov 2012

Maintained deep familiarity with client data assets through ongoing communication and requirements gathering with client stakeholders.

Managed end-to-end data maintenance, integration, and quality assurance using both internal client systems and external third-party data sources.

Enhanced client understanding of customer purchase behavior by developing analytical views, trend analyses, and segmentation insights.

Delivered actionable recommendations by transforming raw client data into meaningful narratives that supported marketing strategy and customer engagement. Catalina USA (Schaumburg, IL)

Predictive Modeler Feb 2011 - Mar 2012

Built predictive and statistical models supporting personalized promotions, targeting strategies, and campaign optimization.

Partnered closely with business teams to interpret model outputs, ensuring actionable insights aligned with marketing and shopper engagement objectives.

Advised stakeholders on promotional measurement methodologies, including lift analysis, incremental impact estimation, and test-vs-control design.

Became a subject-matter expert on Catalina’s extensive shopper, purchase, and loyalty datasets, enabling rapid data mining and advanced analytics.

Contributed to data-driven initiatives that enhanced customer targeting, offer effectiveness, and retail/CPG marketing outcomes.

Education

M.S., Applied Statistics - DePaul University 2008 - 2010

B.A., Psychology - California State University, Northridge 2005 - 2006 Certifications

Google Cloud Digital Leader Certification

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