Dr. Jennifer Prendki

Google DeepMind

Building DeepMind's AI Data Platform and Department. 
Leading and coordinating initiatives in Data Governance, Safety and Infrastructure for Generative AI and LMMs (including Gemini).

Head of AI Data

Alectio

Founder & President

Pioneering the DataPrepOps (a term I coined in January 2021) space and using MLOps + AI to automatically prepare, curate, tune and optimize ML training datasets for specific use cases and models.

Check us out today: https://www.alectio.com

Founder & CEO

Various Startups

The companies I currently advice include Mimoto AI, Mpathic and robotics company inGen Dynamics. 
Past companies: Veamly, VoiceMe, among others.

Advisor / Fractional Chief AI Officer

International Institute for Analytics

- Educating strategists and executives from Fortune 1000 on AI Data Strategy and MLOps
- Helping companies build and scale best-in-class ML teams

Expert and Advisor

Figure Eight

Figure Eight (known by most as CrowdFlower) was the first company to offer enterprise-grade labeling solutions to ML teams. I built and grew the team and Technology that led the company to a $300M acquisition by Appen within a year of my hire. I left the company to focus on the larger problem of Big Data.

VP of Machine Learning

Atlassian

I built Atlassian's first centralized Machine Learning function from scratch and ran the Search & Smarts team, a cross-functional team in charge of developing all Machine Learning-powered features for all Atlassian products.

I grew a world-class team of data scientists and engineers from 3 to 17 people in less than 6 months, across 3 locations (Mountain View, San Francisco and Sydney).

Products developed by my team:
- Cross-Product Search: Centralized Search Engine to search across all Atlassian products
- User Search, Smart Mentions, Recommendations, News Feed

Chief Data Scientist, Head of Search & Smarts Engineering

@WalmartLabs

Managerial experience:

As a member of the Search team, I managed two teams:

- the Metrics-Measurements-Insights team, a group of 9 people (including product managers, engineers and data scientists), in charge of advancing the usage of data and ML best practices within Search. This team also included our Human Evaluation team in charge of preparing training data for the rest of the department.
- the Store-Search team, a cross-geo virtual team of 5 data scientists from both Walmart stores and Walmart eCommerce, the very first initiative at Walmart aiming at democratizing the usage of data from Walmart Stores to improve the algorithms used on Walmart.com

Team projects:

- Metrics development: our team developed key metrics for the organization, such as item findability, customer satisfaction, diversity and perception indexes, using both advanced analytics strategies and ML.
- Machine Learning Lifecycle Management / Automated Model Management: the team developed tools to enforce and automate ML best practices and manage models without the need for human intervention and accounting for systems performance and cost.
- Browse Ranking: the team's new solution increased the revenue coming from browsing customers by ~10%.
- Human and Computer Evaluation:  our team created active learning algorithms that cut in two the volume of data that the Search Department originally had to be evaluated manually.
- Stores-Search: the team developed multiple signals and indicators based on Walmart Stores data to improved the accuracy of the company's Learning-to-Rank models.

Personal projects:

- Review Analysis: I invented an advanced strategy using Post-Purchase Customer Feedback to advise customer purchases (3 patents covering the technology).
- Various projects to advice the Data Strategy of the Department and guide Product Development.

Keywords: Predictive Modeling, Reinforcement Learning, Search, NLP, Metrics, Insights, Analytics

Sr. Data Science Manager & Principal Data Scientist

Ayasdi

Ayasdi is a Machine Intelligence company that uses Topological Data Analysis (TDA) as an innovative way to complement traditional statistical techniques in data analysis and machine learning.

As a member of Ayasdi's world class Data Science team, I worked both as on pushing the boundaries of the software and on researching new ways to leverage its capabilities when solving real-life problems.

- I worked on all kinds of business problems, from looking for outliers to analyzing customer behavior. The industries I've worked with range from retail, social media to cyber security and the financial industry.
- I developed code to automate data preprocessing and investigated data fusion solutions.
- I actively contributed to the design, development and scalability of Ayasdi's machine learning framework.

Keywords: Topological Data Analysis, Graph Theory, Clustering, Outlier Detection, NLP, Persistent Homology, Data Fusion, Deep Learning

Principal Data Scientist

YuMe

Leadership/managerial experience:

As the founding member of the Data Science and Engineering team (which I grew to 8 people in 9 months), I lead all data initiatives, built the roadmaps and acted as the team’s spokesperson. I also worked closely with the executive team on collecting more data features to increase the diversity of the company's data, and build a stable data function.

Technical experience:

My responsibilities covered a large range of Data Science problems, such as forecasting, supply allocation, fraud detection, customer acquisition, etc. Here are some of the projects I worked on:

- Design of multiple algorithms to classify our publisher inventory, based on NLP (Bag-of-words and n-gram models)
- Prototyping, development and deployment of the company's fraud detection system.
- Prototyping, engineering and deployment of YuMe’s inventory forecasting algorithms using Latent Class Modeling.
- Development of a scalable supply allocation system using an hierarchical clustering approach.
- Others: user and family-level fingerprinting, design of attention and receptivity classifiers, trend analysis-based targeting tools.

Keywords: Machine Learning, Data Analysis, Data Science, NLP, Taxonomy, Clustering, Pattern Recognition, Forecasting, Fraud Detection, Supply Allocation, Genetic Algorithms

Senior Data Scientist - Tech Lead

Quantlab Financial

My job at Quantlab Financial consisted in maintaining and enhancing fully automated market microstructure models and trading algorithms, and assisting the traders in the choice of parameters/indicators to be used in their daily strategies. This involved both development of new algorithms and maintenance of existing code and strategies.

My most exciting project was the conception, prototyping and development from a range of NLP algorithms aiming at forecasting short-term market price movements by analyzing information found in news articles and social media (using sentiment analysis and topic modeling).

Keywords: Time Series, PDE, Hidden Markov Models, NLP, Text Mining, Sentiment Analysis, Information Retrieval, Topic Modeling (Latent Dirichlet Allocation), PCA

Quantitative Research Scientist - Machine Learning and NLP

Who am I?
=========

I am an AI Data Strategist, an AI innovator, and a builder. I am serial inventor (20+ patents) and a serial speaker (250+ talks). I take great pleasure in envisioning the future of AI and in evangelizing it. 

As a leader, I specialize in bootstrapping early-stage data initiatives (especially under time- and cash-constrained situations), and in steering dysfunctional ones. I like to call myself an "AI wartime strategist", and companies consult with me to design winning data strategies in all types of environments (collaborative or adversarial, small or large orgs, tech and non-tech companies).

As a people leader, I am highly comfortable managing hybrid teams which include a blend of researchers, engineers and PMs. I've also managed pure engineering teams including frontend, backend and DevOps and love putting order in chaos. I believe in leading by example and in helping people achieve their full potential. I strongly oppose micro-management and believe in empowerment through trust and partnership. I value complete transparency, and I am not scared to say aloud what others keep to themselves. People say I am a no-nonsense person.

I am also a keynote speaker and have spoken at most major conferences in the field. Being a role-model to the younger generation of women in Tech is a big part of my mission. I am proud to say that I have inspired many young women to start a career in STEM. 

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The companies I currently advice include cybersecurity startup Mimoto and robotics company inGen Dynamics. Past companies: Veamly, VoiceMe, among others.

Taplio

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