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When I was an 8-year-old, I was once asked, “What do you want to do in life?” I simply answered, “I want to do cool stuff.” As an adult, that same sentiment has become a key life mantra (albeit using more professional language :-) ). Today, I am a seasoned and extremely technical data science leader with 10+ years of battle-tested experience, leading cross-functional teams of data scientists, ML practitioners, business stakeholders, software engineers and SMEs across dozens of AI projects at 4 different companies. I have also created 7 different open source projects relating to GenAI, ML and football game simulation that can be viewed publicly within my Github repo.And I’m hungry for MUCH more!My journey spans a wide variety of business-critical endeavors including: Generative AI Mastery: Spearheading projects such as developing a generative AI data analysis web application that doesn’t require any technical experience to leading an effort to deploy an LLM model to production.ML Model Prowess: I've constructed and integrated 8 supervised and unsupervised ML models into production applications, contributing to the advancement of data-driven decision-making.Democratizing AI: Whether crafting customer-facing web applications or internal tools, I've championed the democratization of AI, empowering stakeholders to harness its enormous potential.Thought Leadership: I’ve represented multiple companies at Engineering kickoffs, internal and external conferences, hackathons, podcasts, interviews and other important company events.Strategic Collaborations: Engaging with a multitude of companies, including generative AI startups, data science cloud leaders and enterprise technology companies, I've played a pivotal role in shaping AI strategies and forging meaningful partnerships.Innovative Contributions: My endeavors extend beyond project execution; I've authored publications and am working on filing 3 IP disclosures, showcasing novel algorithms in domains like sales forecasting and generative AI.
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Ai EngineerEcue AiDenver, Co, Us -
Principal Data Science Engineer - LeadershipXactly Corp Jun 2020 - PresentLos Gatos, California, UsSince 2020, I have led dozens of cross-functional teams of data scientists and SMEs across 30+ machine learning, statistical and AI engineering projects. I regularly collaborate with leaders from Engineering, Product, HR, Infosec and Marketing.I've led the implementation of 3 different GenAI projects regarding (a): SQL generation, which powers a chatbot integrated into Xactly Extend that sales reps and managers can use to ask questions about commissions and payments. We have achieved an accuracy of 97.7%! (b): automated data analysis, which allows anyone to manipulate a dataset, without needing ANY SQL, Pandas or programming knowledge of any kind (c): customer support ticket classification, which allows a ticket to be placed into its correct queue without needing any manual intervention.I have also directed the planning, implementation and testing of 6 machine learning models, including end-to-end development of pipelines, data cleaning code, and deployment to customer-facing production environments.Finally, I have represented Xactly publicly in the following ways:(1): I participated in 2 data science hackathons involving 120+ people and 30+ companies each, winning $6,000 in prize money and implementing 2 separate minimum viable products (MVPs). 1 MVP got backing from leaders at Vista Equity Partners, the private equity firm that financially supports Xactly. (2): I appeared on the Tech Talks Daily Podcast with Neil C. Hughes on 12/2022 to promote Xactly's sales compensation plan management software and to discuss data science. (https://techblogwriter.co.uk/xactly-corp/)(3): I appeared on an interview with the Enterprisers Project in 8/2022 discussing a day in the life of a data scientist. (https://enterprisersproject.com/user/jeffrey-partyka)I have also made available 7 different GenAI and data science projects in my GitHub repo - the link is available in the hard copy of my resume. -
Principal Data Science Engineer - Technical AccomplismentsXactly Corp Jun 2020 - PresentLos Gatos, California, UsI managed, implemented and tested the following machine learning projects:- A Python-based SQL generation Generative AI web service, capable of leveraging either GPT-4 or Llama2-70B to generate SQL queries for customer use. Implemented a query cache utilizing the voyage-lite-02-instruct embedding model to provide consistent and correct responses to past queries, reducing costs by minimizing prompts to GPT-4. Engineered an automated feedback system allowing users to upvote/downvote LLM-generated answers, with highly-rated SQL queries automatically placed into the query cache.-A sales forecasting ML model integrated into Xactly Forecasting, awarded "Best Predictive Analytics Solution" at the 2023 AI Breakthrough Awards. Achieving an average 96% accuracy, 95% F1, and 94.5% ROC-AUC across 20 customers, the model informs sales strategies for Xactly executives and teams. Auto-machine learning techniques enable daily recalibration, incorporating new data and engineered predictors while maintaining high performance. Opportunity and company-level predictions and explanations are seamlessly integrated into the Forecasting customer dashboard.-A sales new hire success prediction model in collaboration with HR, utilizing historical sales revenue data and psychometric sales assessments to forecast Xactly sales new hire success. Built a streamlit web application on AWS for HR to conveniently generate predictions and explanations for new hires individually or in batches. -A sales rep attrition model integrated into Xactly Insights that predicts turnover for 50+ companies weekly. Revamped the model for our team's Databricks platform and company's Snowflake data warehouse, and deployed it across 10 production environments.-Developed a churn model for predicting Xactly contract renewals, aiding CSM leaders in optimizing customer retention.-Developed a cross-selling model that used a genetic algorithm to identify cross-sell and upsell opportunities.
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Lead Research And Data AnalystWndyr Mar 2020 - Jun 2020Houston, Tx, Us -
Research And Development ManagerInfor Aug 2017 - Mar 2020New York, Ny, UsDesigned and/or implemented 66.7% of Science department apps (14/21) over 888 commits in Python, while helping the development team productize 3 of those apps into Java. Also, single-handedly built the entire backend infrastructure for the team and delivered 3 series of lunch and learn presentations on SQL, Hadoop and machine learning. Highlights include:- Designed, implemented and helped productized our award-winning Team Dynamics app, which won “Most Innovative New App” award at HRTech 2017, beating out Google and others. The tool calculates an Overall Team Chemistry Score for any team built from our D3- enabled UI, while providing supporting individual-level psychometric analytics and visualizations - Built, tested and helped productized a flight-risk logistic regression model, predicting the probability of employees in a company leaving their job 3 months, 6 months and 12 months out- Designed and implemented a cognitive item prototype using HTML5 Canvas/JavaScript capable of auto-generating over 2.75 billion distinct shape-pattern problems for employee assessments, several times more than any other product in the HR analytics industry. A paper describing this tool was accepted into SIOP 2020, the top I/O psychology conference- Built prototypes for a small HTML5 Canvas-based video game representing an interactive assessment item, computer-vision based academic paper parser guiding R&D’s product roadmap, and NLP analytics tool over full text employee data using WordNet-based clustering- Designed an R&D process flow to organize a department-wide approval process for new app and predictive model ideas.- Designed a survey-oriented, highly technical interview process evaluating machine learning, data science and software engineering abilities, as well as behavioral fit. Multiple candidates have stated that our interview was the best in which they ever participated -
Senior Software R&D Developer/Big Data/Data ScientistInfor Jul 2014 - Aug 2017New York, Ny, UsDesigned and/or implemented 66.7% of Science department apps (14/21) over 888 commits in Python, while helping the development team productize 3 of those apps into Java. Also, single-handedly built the entire backend infrastructure for the team and delivered 3 series of lunch and learn presentations on SQL, Hadoop and machine learning. Highlights include:- Designed and implemented Cloud Analytics, a 40K LOC statistics engine written using Python’s Django framework, HTML/CSS/Javascript, JQuery and Raphael.js. This has allowed our Data Analysis team to conduct 68 hiring and termination studies demonstrating the long-term effectiveness of our personality assessment to clients. Key features include the application of χ 2 tests of independence over aggregate and targeted samples and the ability to measure correlations by any one of dozens of variables. DAs complete studies 4x faster than before - Created and managed our Science Cloud environment on AWS, composed of 4 CentOS 7 instances: the app server containing Science’s dev, test and prod codebases, a Postgres 9 database instance containing Science’s dev, test and prod databases, a SQL Server instance containing the dev team’s prod database and a git repo server. Implemented all ETLs between the SQL Server instance and Postgres instance, moving 3+ billion rows to Postgres. Also wrote all web server and git code deployment scripts using bash, cron and other linux tools- Gave 12 lunch and learns to the Science department regarding SQL, linux command line tools for data science, Hadoop, an overview of machine learning and GDPR best practices
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Adjunct Professor, Semantic Web And Semantic ComputingUniversity Of Texas At Dallas Jan 2014 - Dec 2014Richardson, Texas, UsCreated all course content, did nearly all grading, prepared and delivered lectures for a graduate level Semantic Web course. The class was made up of 57 students, and it covers topics such as RDF, SPARQL, OWL, ontology alignment and semantic similarity. Assigned a class project involving the merging and visualization of heterogeneous datasets using the Linking Open Government Data portal (http://logd.tw.rpi.edu/). -
Data Scientist/Big Data Software EngineerRaytheon Dec 2011 - Jul 2014Arlington, Va, UsDesigned and implemented numerous text processing analytics as part of IR&D projects and established programs by utilizing Hadoop, HBase, Pig, Stanford NER, and other open source tools over tweets, landmark data, and unstructured text. Also evangelized data science, machine learning algorithms and Big Data technologies across Raytheon via brown bags, IR&D and DARPA challenge proposals and a submission to SIAM ‘13. Accomplishments include:• Lead data scientist on IR&D effort since Nov. 2013 for developing a multi-intelligence fusion capability that generates analytics over terabytes of open source datasets. Wrote MapReduce job implementing patterns of life, associating Tweets with latlon coordinates using geohashed rowkeys in HBase. Also created analytics for calculating the probability of pairs of Twitter users being in the same location at the same time and identifying “lone wolf” users • In support of a high-profile program, wrote MapReduce jobs to implement large-scale entity enrichment of DIB data using Stanford NER, and wrote a recommendation capability to link DIB records through their representative entity vectors by employing semantic similarity • Authored publication entitled, "MagicEye: A Big Data Approach to Activity Based Intelligence", that described MapReduce and Pig jobs performing large scale data association of over 75M geolocated tweets with SimpleGeo landmarks using latlons. The paper was submitted to SIAM 2013 • Wrote 4 Raytheon proposals between July 2013 and March 2014 describing (1: a company- wide deployment of Probabilistic Graphical Models (PGMs) over program codebases (2: a recommendation engine customized for intelligence analysts (3: the use of real-time analytics generation using Apache Storm to expand our multi-INT fusion capability. (4: Applying Latent Dirichlet Allocation and other topic models over social media data -
Software DeveloperBank Of America Merrill Lynch May 2011 - Dec 2011Design, develop, test and deploy various financial applications using object-oriented C++/win32 programming. I was 1 of 2 interns selected for the internship, out of 113 that applied. (1.8% acceptance rate). The projects utilized object-oriented design, design patterns, graphics and interface programming, financial analytics, the FIX protocol, order and exchange informatics, and more.
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Research AssistantUniversity Of Texas At Dallas Aug 2007 - Nov 2011Richardson, Texas, UsResearched, implemented and published innovative algorithms coded in Java in the areas of geospatial ontology alignment, schema matching and data analytics, resulting in being the first author of 7 publications at top conferences and journals. Accomplishments include:• Published the following: - Learning-based Geospatial Schema Matching Guided by External Knowledge (dissertation) - Enhanced Geographically-typed Semantic Schema Matching (Journal of Web Semantics) - Content-Based Geospatial Schema Matching Using Semi-Supervised Geosemantic Clustering and Hierarchy (ICSC 2011 at Stanford University) - Content-based Ontology Matching for GIS Datasets (ACM GIS 2008) - Ontology Matching by Exploiting Structure Using EM in GIS Datasets (ISWC 2008) - Semantic Schema Matching Without Shared Instances (ICSC 2009) - Geographically-typed Semantic Schema Matching (ACM GIS 2009) • Created the following projects, all coded in Java: - Schema/Ontology Matcher Using Instance Matching Analytics and Entropy-Based Distribution 1:N Bottom-Up Ontology Matching Program - Minesweeper Solver Using Knowledge-Based Reasoning to Solve Any Game with a Solution - Baseball Quality Start Analytics Classifier Using Naïve Bayes, KNN and Neural Networks
Jeffrey Partyka, Ph.D. Skills
Jeffrey Partyka, Ph.D. Education Details
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The University Of Texas At DallasComputer Science -
University Of Texas At DallasComputer Science
Frequently Asked Questions about Jeffrey Partyka, Ph.D.
What company does Jeffrey Partyka, Ph.D. work for?
Jeffrey Partyka, Ph.D. works for Ecue Ai
What is Jeffrey Partyka, Ph.D.'s role at the current company?
Jeffrey Partyka, Ph.D.'s current role is AI Engineer.
What is Jeffrey Partyka, Ph.D.'s email address?
Jeffrey Partyka, Ph.D.'s email address is je****@****las.edu
What is Jeffrey Partyka, Ph.D.'s direct phone number?
Jeffrey Partyka, Ph.D.'s direct phone number is +121470*****
What schools did Jeffrey Partyka, Ph.D. attend?
Jeffrey Partyka, Ph.D. attended The University Of Texas At Dallas, University Of Texas At Dallas.
What are some of Jeffrey Partyka, Ph.D.'s interests?
Jeffrey Partyka, Ph.D. has interest in Novel Writing, Baseball, Preparing For Jeopardy, Radio Broadcasting, Creating Electronic Music.
What skills is Jeffrey Partyka, Ph.D. known for?
Jeffrey Partyka, Ph.D. has skills like Java, Hadoop, Mapreduce, Eclipse, Javascript, Git, Apache Pig, Mysql, Maven, R, Css, Perl.
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