Vera Kalinichenko

I bring a unique blend of rigorous mathematical expertise, rooted in my time at the Ph.D. program at UCLA, and extensive real-world experience from working at renowned startups like The Honest Company, Headspace, AtomTickets, and FabFitFun. My journey began as a software engineer, spanning from 2000 to 2012, which equipped me with a solid foundation to transition in 2012 into the world of data science.

Over the years, I've pioneered several innovative data-driven solutions.

Notably, I've architected recommendation engines from the ground up, devised retention models to enhance user engagement, and implemented sophisticated algorithms to detect fraudulent activities.

My dedication to the field is also reflected in my publications.

One of my notable works explores the application of genetic programming to e-commerce,

while another delves into harnessing the power of embedding techniques from LLM to provide real-time answers to consumer queries about inventory.

When discussing data science products with CEOs and stakeholders, I emphasize not just the technical intricacies but also the tangible business impacts and transformations they drive.

Data Science and ML

• Dynamic Pricing 
• Markov Models
• AWS Fraud Detection
• Data Anomality Discovery
• Survival Analysis
• Neural Nets
• Image Processing
• Few-shot learning
   
• Personalization
• Recommendation Engines
• Time Series Analysis (ARIMA, SRIMA)
• Pareto, Poisson and Binomial Probabilistic Distributions
• Lead Nurturing for retail, automotive space
• Customer Segmentation
   
• Genetic Programming
• Bayesian Optimization
• Multi-objective Optimization with GUROBI, PULP
• Pricing Solutions for e-commerce as optimal PtM
• A/B Testing

Director of Data Science at Shift 

• Hired and led geo-distributed team of data scientists and software engineers. 
• Mentored career path development, performance evaluations for managers and senior IC’s improved talented retention by 25%. Team Budget.
• Developed and owned a cross-functional data science roadmap for Pricing System, Inventory Mix and backend ad on products which improved product maintainability by 70%.
• Designed and launched vehicle recommended add on pricing products such as VPP, APP, Offer Recommended Price, Final Sale Price, Days to Sell.
• Designed, launched and managed successful execution of Data Science roadmap including distressed inventory, vehicle similarity, shelf space optimization on the car listing site that improved GPU per vehicle by 25%.
• Developed and launched customer inquiry responses leveraging text embeddings; experimented with sentence transformers from 364 to 768-dimensional space, identified metrics suited for automotive space to identify nearest neighbors. Adapted the question/response solution in HubSpot and Twilio lead nurture use case.
• Setup AWS SageMaker environment for the data science team, maintained AWS lambdas, AWS SageMaker FeatureStore. Introduced ML Platform  for Shift which led to ML product  delivery improvement by 70%.

Director of Data Science and Analytics at Disqo

• Hired and led a geo-distributed team of data scientists, data analysts and data engineers. 
• Developed and owned a cross-functional data science and analytics roadmap. Managed overall ML architecture, business logic implementation for internal and external ML driven data products.  
• Led Fraud Detection and Prevention initiative. Developed in-house machine-learning strategy to detect fraudsters in the online market research, launched the fraud detection product and worked with customer facing teams to integrate the fraud detection into real time production system.  Leveraged AWS SageMaker Endpoints to deliver user level fraud score in real-time. 
• Designed and launched successful panelists engagement internal product such as panelist churn forecast, panelist lifetime value forecast, user segmentations.
• Owned and delivered on data science, analytics and engineering OKRs reduced panelist attrition by 25%, improved quality of survey completion by 40%.
• Published in IntelliSys - Fraud Detection in Online Market Research Space.
   

University of California Los Angeles

• BS degree in Mathematics of Computation           

University of California Los Angeles

• MA degree in Applied Mathematics.  Three years of PhD Program in Mathematics (completed all qualification requirements)

Kyiv State University named after T. Shevchenko (Kyiv, Ukraine)

• Pure Mathematics Major