Expert Details
Data Analysis, Data Science, Machine Learning, Algorithms, AI, Ad-tech, and eCommerce
ID: 736354
Illinois, USA
Has led ML/AI/GenAI strategy and engineering at 500 & 100 fortune companies & startups architecting enterprise-scale GenAI platforms and multi-cloud MLOps stacks (Azure, AWS, GCP, Databricks).
She has designed, developed, and deployed a production-grade LLM applications (private deployment). Her toolkit spans Python, Spark, LangChain, RAG pipelines, starting from BERT/GPT/LLaMA to LLMs/GenAI, RL, vector DBs, CI/CD for ML, SDLC, and secure API orchestration, etc. She received the 2024 GenAI Innovator Award and serves as a trusted advisor on scaling responsible AI /GenAI aligned with regulatory, privacy, and business impact requirements.
Education
| Year | Degree | Subject | Institution |
|---|---|---|---|
| Year: 2004 | Degree: Dual Ph.D. | Subject: Physics & Mathematics | Institution: Kirensky Institute of Physics, SB Russian Academy of Sciences |
| Year: 2000 | Degree: Dual M.S. | Subject: Physics & Engineering | Institution: Reshetnev Siberian State Aerospace University |
Work History
| Years | Employer | Title | Department |
|---|---|---|---|
| Years: 2024 to Present | Employer: Undisclosed | Title: Director of Data Science, ML/Gen AI | Department: Data & Analytics |
Responsibilities:• Developed end-to-end AI/GenAI strategies, set short & long-term objectives that accelerate business goals through data and AI solutions.• Spearheaded Smart Digital Transformation, data organization & responsible AI usage across the organization. Conducted gap analyses and risks for tech stack and seamless ML/GenAI development and integrations. • Designed, developed, and deployed AI/GenAI (LLM) software products - including Q&A tools, smart chatbots, semantic matching, and knowledge management systems - using NLP, image/text processing, optimization algorithms, and Databricks across multi-cloud environments. Integrated generative AI into business processes and IT systems, built supporting data pipelines, MLOps, addressing security & data governance, and delivered measurable ROI. • Spearhead Digital Transformation: formulated the development of a comprehensive Digital Data Platform, including a full-stack ML/AI/ MLOps, DataOps, MLOps, and a robust SDLC, CI/CD processes. Cloud agnostic as well as experienced to build on premises. • CPG: developed and led global category management, optimizing vendor selection, contract negotiations, and risk mitigation. Managed end-to-end operations, ensuring efficiency, cost savings, and inventory optimization. • Partnered with 15+ C-suite executives to align data science initiatives with business goals, boosted confidence in AI strategies by 90%. • Ideated, implemented a new forecasting method for GCP compute and Databricks usage, resulting in $1.4 million in cost savings. • Developed training programs & hackathons that boosted ML/AI/GenAI skills and increased team engagement in GenAI projects. • Built, mentored, or coordinated cross-dimensional 40+ people teams across company. • Evaluated cloud platforms (Azure, GCP, AWS) for cost effectiveness and scalability. |
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| Years | Employer | Title | Department |
| Years: 2021 to 2024 | Employer: WALGREENS | Title: Director of Data Science and Artificial Intelligence | Department: HEALTH | WBA AI LAB |
Responsibilities:• Sparked Revenue Growth & Cost Savings: Led the Data Science/AI strategy, transforming business needs into impactful solutions. Delivered ML/AI products that saved $297.5M annually in labor spend and increased dynamic reserve quantity, generating an additional $5.8M in value. Created strategic partnerships and alliances across internal and external partners.• Spearheaded Digital Transformation: conceptualized and oversaw the development of a comprehensive omni-channel patient-centric Walgreens Health (WH) Digital Platform. This included a full-stack ML/AI unit, DataOps, MLOps, and a robust SDLC, CI/CD processes incorporating IoT/Edge AI solutions. Evaluated and optimized cloud platforms (Azure, GCP, AWS) for cost-effectiveness and scalability. • Revolutionized Patient Engagement: built and managed cross-functional teams delivering innovative patient-focused solutions; designed and implemented a Health Learning System (HLS) to optimize care management through an adaptive clinical workflow, patient data repository for comprehensive health data access. Optimized pharmacy operations, AI security. • Secured funding for key data science initiatives, expanding AI impact at WH Healthcare. Built strategic partnerships to accelerate AI adoption. Launched a recommendation engine and coaching chatbot with avatar, improving patient engagement. • Led AI innovations in pharmacy analytics and inventory, cutting costs and boosting efficiency. |
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| Years | Employer | Title | Department |
| Years: 2020 to 2022 | Employer: XEN.AI | Title: Head of Data Science | Department: Data Science and Innnovations |
Responsibilities:• Promoted the Center of Excellence (CoE) for Data Science/ML. Led Tech innovations and delivery using advanced analytical models.• Fostered a culture of cross-departmental cooperation, unlocking the capabilities of Data Science and AI/ML, Edge AI approaches to facilitate the development of meaningful and effective solutions across Xen's range of offerings. Cost analysis. • Led opportunity identification, planning, design, development, implementation of predictive ML/AI models for industrial Supply Chain & eCommerce spaces delivering $30M+ annual impact. • Grown revenue: reduced inventory carrying cost by up to 17%, improved the order accuracy by up to 27% by optimizing inventory for complex supply chain, demand; led time analytics and getting insights for warehouse and material networks. • Increased customer retention rate by 14%, improved customer life value vs. customer acquisition cost as 3:1, grown Net Promoter Score by 8 points using NLP (OCR, LSTM, BERT, GPT-3), RL, speech & image processing, predictive modeling. • Improved provider outreach turnaround time by 10% by identifying the optimal timing and channel for outreach. • Cut costs and raised digital engagement by 8% through predictive analysis and barrier resolution. • Boosted product conversion by 7% through behavioral targeting and churn-reduction strategies. • Technologies: AWS, SageMaker, Lambda, S3, AWS IoT Core, Neptune, Neo4j, d3js. |
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| Years | Employer | Title | Department |
| Years: 2020 to 2022 | Employer: NORTHWESTERN UNIVERSITY | Title: Head of Data Science / SME | Department: Information Systems Programs |
Responsibilities:• Promoted the Center of Excellence (CoE) for Data Science/ML. Led Tech innovations and delivery using advanced analytical models.• Fostered a culture of cross-departmental cooperation, unlocking the capabilities of Data Science and AI/ML, Edge AI approaches to facilitate the development of meaningful and effective solutions across Xen's range of offerings. Cost analysis. • Led opportunity identification, planning, design, development, implementation of predictive ML/AI models for industrial Supply Chain & eCommerce spaces delivering $30M+ annual impact. • Grown revenue: reduced inventory carrying cost by up to 17%, improved the order accuracy by up to 27% by optimizing inventory for complex supply chain, demand; led time analytics and getting insights for warehouse and material networks. • Increased customer retention rate by 14%, improved customer life value vs. customer acquisition cost as 3:1, grown Net Promoter Score by 8 points using NLP (OCR, LSTM, BERT, GPT-3), RL, speech & image processing, predictive modeling. • Improved provider outreach turnaround time by 10% by identifying the optimal timing and channel for outreach. • Cut costs and raised digital engagement by 8% through predictive analysis and barrier resolution. • Boosted product conversion by 7% through behavioral targeting and churn-reduction strategies. • Technologies: AWS, SageMaker, Lambda, S3, AWS IoT Core, Neptune, Neo4j, d3js. |
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| Years | Employer | Title | Department |
| Years: 2020 to 2021 | Employer: UC BERKELEY | Title: Subject-matter expert | Department: School of Information |
Responsibilities:Program: Machine Learning for managers (part time teaching) |
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| Years | Employer | Title | Department |
| Years: 2019 to 2020 | Employer: pEXCHANGE, LLC | Title: Director of Data Science & Artificial Intelligence | Department: Data Science |
Responsibilities:• Developed and delivered the Search engine/Document Database for structured and unstructured information using NLP & ML models like semantic match, OCR, NLTK, Word2Vec, BERT, CNN, GPT-2, GPT-3. AWS, Cloud Computing, Google Analytics, GBQ.• Developed semantic search software solution including ontologies and taxonomy for the client`s specific corpora. • Partnered with 3+ C-suite executives aligning Data Science efforts with business goals; boosted confidence in data-driven strategies by 90% • Established the Center of Excellence (CoE) for Data Science/ML. Advised to CTO, CEO to identify business problems and determine ML solution requirements for business problems as well as strategic planning and cost analysis. • Established, planned, and administered the overall policies and goals of the data science team. • Developed ML semantic match using NLP: sem. similarities, NLTK/Gensim, GloVe/Word2Vec/BERT. • Managing innovative DS and AI projects focused on seeking solutions to real-world problems. • Collaborating with agile teams of full stack engineers. |
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| Years | Employer | Title | Department |
| Years: 2016 to 2019 | Employer: W.W. GRAINGER, Inc., Lake Forest, IL | Title: Sr. Data Scientist-Lead, Marketing, eCommerce/Business Insights, Artificial Intelligence | Department: Data Science and Analytics |
Responsibilities:• Elevated the Center of Excellence (CoE) for Data Science/ML into a centralized team dedicated to providing services to various departments within Grainger. Drove Marketing, eCommerce/Business Insights, Artificial Intelligence initiatives.• Ideated the methodology of the Cohesive Real-Time integration MRO omni-channel platform using combination of multiple identifiers across data points (including clickstream) collected for smart marketing & recommendations that drove sales and boosted ROI. • Designed and developed the product Recommendation Engine (RE) that fueled business growth and ultimately led to doubling of the Grainger`s stock price from ~$160/share (2017) to ~$360/share (2018). Developed the NLP text matching model as a part of RE. • Ideated and developed predictive models using Markov chains and RL to boost engagement, ROI, and customer acquisition. • Developed the optimized CNN architecture (Deep Learning) for real-time image detection and classification. • Led projects end-to-end; interviewing people; working with business partners and intellectual property team. • Developed semantic match model using NLP, NN, Machine & Deep Learning, Word2/Doc2Vec, Semantic Similarities. • Dramatically improved a product recommendation engine by developing a model for predicting risk of Revenue decline. • Developed association rules for up- and cross-selling based on viewed and purchased products (clickstream data) that significantly improved customer experience on www.grainger.com. • Modeled negotiation outcome (Cost Support); developed algorithm for Sentiment Analysis of surveys. • Derived a new method based on SVD for working with sparse matrices; developed Web scraping code. • Programming/code mgt.: Python/SPARK, R, Excel VBA, Git/BitBucket, Shiny/Theano/Keras,/TensorFlow, Tableau. • Dev. env.: Windows/Mac/Unix, GPU, PyCharm, PyTorch, H2O, VSC, R Server; Data: Teradata, SQL, Hadoop. |
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| Years | Employer | Title | Department |
| Years: 2014 to 2016 | Employer: CENTRO, Inc., Chicago, IL | Title: Predictive Analytics Data Scientist | Department: Data Science |
Responsibilities:• Led scope definition and team building for predictive modeling and product development; built and scaled the Data Science team. Applied models to boost ROI and KPIs for ad campaigns (Centro, Facebook), including viewability, audience scoring, and campaign optimization.• Developed Ads Optimization, click prediction, and audience models for online advertising using Centro's and external data, optimization, clustering and classification algorithms. • Performed Quantitative Research, Predictive Statistical Modeling, Model Validation, including Linear Mixed-Effects, Uni-/multivariate and Factor Analyses, Logistic Regression, Random Forest, Collaborative Filtering, Neural Networks, Real Time Analytics, Web Analytics. • Analysis of user cookie-level data and Real-time bidding data (multi-TB scale) using Amazon S3, Hadoop cluster with Spark, Spark MLLib, Hive and Python. • Found new modeling approaches for Real-time bidding via programmatic instantaneous auction, similar to financial markets, to know problems and realize it as a software tool that paved the way to profitable click predictions. • Performed time series analysis, dynamic linear modeling, content-based recommendation, value-added models, and probabilistic record linkage involving Big Data and Machine Learning, Bayesian statistics, probabilities, Markov chain Monte Carlo techniques. • Built real-time bidding models using cookie-level data and RTB auction dynamics; developed Spark streaming daemons enabling 10ms ad transactions. Created advertiser-publisher scoring and recommendation engines using CF, SVD/iSVD, LFM, and Markov chains to enhance targeting. • Designed behavioral targeting, ad optimization, and click prediction models for omnichannel identity resolution across devices and touchpoints. Proposed new SaaS-based real-time bidding approaches for programmatic auctions. • Tools & Tech: Python, Spark, R, C#, MATLAB, VBA, Cypher, Hive, S3, Hadoop, MLLib; DBs: SQL, Pentaho, PostgreSQL, NoSQL (MongoDB, Cassandra, Neo4j). • BigData processing with Hadoop, HDFS, programming using Spark, MapReduce, Pig language. • Programmed: Python, SPARK, R, C#, Excel VBA, Cypher, Matlab. • Agile development environments: Windows, UNIX, Mac. |
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| Years | Employer | Title | Department |
| Years: 2012 to 2014 | Employer: CME GROUP, Inc., Chicago, IL | Title: Quantitative Risk Research Consultant promoted to Sr. Risk Management Analyst | Department: Clearing House |
Responsibilities:• Performed risk analysis: Greeks, VaR, HVaR, Expected Shortfall (CVaR), tail risk, stress testing, CCAR, SPAN, pricing, volatility DB. Asset classes: Commodities, Fixed Income, OTC, IRS, CDS, Futures/Options, Swaps, FX, Equities & Cross-Margin accounts.• Performed time series, seasonality, statistical analysis of data. Collaborated with IT to enhance data quality for modeling and compliance. • Developed Real-Time Market Risk dashboards; collaborated with DevOps on real-time trading analytics tools. • Modeled Energy and Liquidity risk for commodity derivatives using GARCH, EWMA, ARMA. • Programmed extensively in MATLAB, Excel VBA, R, C#, and SQL. |
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| Years | Employer | Title | Department |
| Years: 2008 to 2012 | Employer: CARNEGIE INSTITUTION FOR SCIENCE | Title: Research Analyst Associate | Department: Geophysics |
Responsibilities:• Led multiple end-to-end research projects, supervised 3 interns/young scientists, and secured competitive grants (DOE, NSF, APS).• Analyzed scientific data using theoretical models in quantum mechanics, condensed matter, and geophysics; applied Monte Carlo methods, Python, and spectroscopy techniques. Built data-level testing tools and discrete event simulation models for scientific equipment communication and analysis. |
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| Years | Employer | Title | Department |
| Years: 2005 to 2008 | Employer: ARGONNE NATIONAL LABORATORY | Title: Post-Doctoral Researcher | Department: U.S. DOE Energy's Office of Science |
Responsibilities:• Coordinated work of 2 summer interns/young scientists. Leader of the end-to-end projects; wrote and won grants for scientific projects proposals at Department of Energy, American Physical Society, National Science Foundation, etc. Tested theoretical predictions of contemporary models related to the properties of magnetic materials.• Digital signal processing, synchrotron spectroscopy, regression, Monte-Carlo to extract critical information from experimental data. • Modeled and simulated complex dynamical properties (Fortran, MatLab, Python); UNIX/LINUX. |
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Career Accomplishments
| Licenses / Certifications |
|---|
| • Certificate, Exercising Leadership. Harvard University, 2024 • Certificate, Intel Edge AI Developer (IoT). Intel®, 2022 • Certificate, Global Leader, Manage Mentor Leadership Solutions, Harvard University, 2017 • Big Data TechCon, Certificate of Completion (San Francisco, 2014) • The Caltech-JPL Summer School on Big Data Analytics (Caltech) • Machine Learning (Stanford University, 2014) • Global Emerging Leader program (Harvard University, Manage Mentor Leadership Solutions) |
| Publications and Patents Summary |
|---|
| She is a primary author or co-author of more than 20 scientific papers published in major peer-reviewed physics journals, 1 granted and 1 pending patent. |