Jack Maney

Email: jackmaney@gmail.com

Website: jackmaney.com

  • Data Science and Data Engineering professional with a decade of experience in the telecommunications, ad tech, financial service, and healthcare sectors.
  • Able to derive insights and extract business value from data sets with thousands to billions of rows.
  • Building prototypes of data products using relational databases, Apache Spark, MPP systems, and Python
  • Working closely with Data Engineers to productionalize product prototypes.
  • Researching and implementing algorithms from white papers and academic literature.
  • Creating and A/B testing recommender systems.
  • Experienced problem-solver with very strong quantitative skills.

Experience

American Century Investments

Senior Data Scientist - October 2023--October 2024

  • Created and productionalized an Engagement Score for financial advisors.
  • Took over maintenance of an existing production recommender system.
  • Restructured parts of a Data Science monolithic repo, consolidating utility functions used in multiple places into a common utility library.
  • Ran several ad-hoc analyses, some of which were under very strict deadlines.
  • Technologies Used: Python, Amazon Redshift, pandas, scikit-learn, boto3, Salesforce API, AWS, AWS Secrets Manager, AWS Lambda, S3, Tableau, git, GitHub

nbkc bank

Senior Data Engineer, AVP - November 2022--September 2023

  • Did a nearly complete rewrite of the back-end for tracking movement of customers among segments. Using an object-oriented design, the addition of new segments or changes to existing segments are now much easier to implement.
  • Built a heuristics-based approach for determining whether an ACH credit is a direct deposit.
  • Altered Power BI dashboard of internal expenses to correctly show sub-account transactions. Assisted in showing results to the CFO and gathering feedback.
  • Fixed incorrect assignments of Personal/Business accounts for survey data from customers.
  • Automated a report used by the Deposits team.
  • Used the Salesforce API to send emails when certain events are triggered.
  • Mentoring members of the Data Team.
  • Technologies Used: Python, pandas, Azure DevOps, Apache Airflow, Cosmos DB, Azure Key Vault, Ramp API, SurveyMonkey API, Power BI, git

Shopify

Data Scientist - June 2022--September 2022

Before being laid off, I was part of the Plans & Pricing Data Science team.

  • Helped identify suspicious leads by implementing a markov chain to detect gibberish subdomain names.
  • Took over the (manually run) referral program and worked with data engineers to automate this process.
  • Technologies Used: Python, GCS, git

agilon health

Lead Data Scientist - July 2021--June 2022

  • Worked on models to predict avoidable inpatient visits and medication adherence.
  • Worked with the ML Ops team to validate datasets that have been moved to the Cloud.
  • Technologies Used: Python, pandas, scikit-learn, S3, AWS SageMaker, git

Cerner Corporation

Data Scientist - July 2020--June 2021

  • Used AWS SageMaker, BlazingText, and association rule mining to analyze and enhance the Chart Assist Ontology. Created a prototype that could make terminologists up to five times more efficient at matching medical codes to related ontology concepts.
  • Technologies Used: Python, pandas, XGBoost, AWS Sagemaker, BlazingText, git

TruFactor

Lead Data Scientist - November 2018--May 2020

After Pinsight Media was acquired by InMobi, there was a reorganization into a few business units, one of which was TruFactor.

  • Consolidated Point of Interest (POI) data from multiple sources to build a single POI database used across the company.
  • Combined the POI dataset with GPS and network location data to build a Visits dataset. Worked closely with product managers to ensure that the product aligned with customer expectations. Performed several white glove analyses for customer trials, which received positive feedback.
  • Worked closely with Data Engineering to productionalize the Visits product, and to quickly deploy hotfixes and feature enhancements.
  • Used multiple data sources--including scraping and third-party APIs--to build and maintain a mapping from URLs to publishers.
  • Mentored members of the Data Science and Business Intelligence teams.
  • Technologies Used: Python, PySpark, AWS EMR, AWS Lambda, S3, Snowflake, Tableau, H3, plotly, GeoJSON, Aylien API, git, GitHub

Pinsight Media

Data Scientist III - October 2016--October 2018

Pinsight Media was acquired by InMobi in 2018.

  • Built recommender engines for our on-device monetization products. Worked with development teams to ensure that the back end would be set up for AB testing.
  • Streamlined the ETL processes for building AB testing dashboards.
  • Contributed to a project of predicting demographic attributes for users in our real-time bidding (RTB) system. This resulted in collaborations with Marketing that led to two whitepapers:
  • Mentoring members of the Data Science and Business Intelligence teams.
  • Technologies Used: Python, PySpark, AWS EMR, AWS Lambda, S3, Snowflake, 42matters API, Tableau, git, GitHub

DST's Applied Analytics Group

Senior Data Scientist - December 2013--October 2016

  • Prototyped a product for acquisition of financial advisors.
  • Contributed towards an Advisor Segmentation product, including a method of streamlining and summarizing the differences between segments.
  • Built a prototype of the Mapper Algorithm (as used in Topological Data Analysis) to better understand high-dimensional data sets. The prototype is written in Python and leverages a Greenplum cluster by way of SQL templates.
  • Built prototypes for three components of DST's Predictive Wholesaling product, and assisted the AAG Development team in productionizing the prototypes.
  • Created and prototyped a Share Retention metric that provides a measurement of "stickiness" of fund holdings that does not directly depend on price.
  • Assisted in building models for a proof of concept for a client.
  • Mentored and taught Python to a few members of the Networking team, to facilitate the creation of a Flask web app to automate some types of network change requests.
  • Mentoring other members of the Data Science team.
  • Technologies Used: Python, Pivotal Greenplum, pandas, scikit-learn, git, Assembla

BA Services

Data Scientist - May 2013--November 2013

  • Created and cross-validated probit regression models to find the most significant attributes upon which to sort call queues in order to increase customer retention.
  • Built an ETL pipeline to import data from a new dialer system.
  • Delivered a proposal outlining options for a Data Warehouse solution, including pros and cons of each option.
  • Built, Validated, and Deployed business intelligence reports using QlikView.
  • Technologies Used: Perl, QlikView, SAS, SVN

C2FO

Implementation Specialist (Contract) - January 2013--May 2013

  • Optimized the C2FO algorithm for Market Clearing Events, making it run an average of two orders of magnitude faster.
  • Organized the restructuring of several KPI business intelligence reports.
  • Built, tested, and deployed user management tools for account managers.
  • Technologies Used: Perl, Ruby

Adknowledge

July 2010--November 2012
Titles Held:
  • Sr Data Analyst and Mathematician - January 2012--November 2012
  • Data Analyst and Mathematician - February 2011--January 2012
  • Data Analyst - July 2010-February 2011
  • Performed data mining and summarized results that contributed to the winning of a $50,000 advertiser contract.
  • Presented technical and mathematical concepts to non-technical audiences, including several layers of management and a venture capital investor.
  • Developed an application in Perl using DBI for k-means++ clustering. This application is able to handle data sets of millions of rows with 1--100 variables.
  • Found a way to implement a regression algorithm--on a dataset with 30 million rows and 250 variables--that was previously thought impossible to implement due to scale.
  • Built, implemented, deployed, and maintained an ad category recommendation system for advertisers, including developing and measuring performance metrics.
  • Implemented a genetic algorithm framework to use for behavioral targeting algorithms.
  • Maintained and documented the ETL pipelines to the Data Analytics team, consisting of over 200 scripts in Perl and Python interfacing with Greenplum, PostgreSQL, Oracle, MySQL, MS SQL, and ActiveMQ.
  • Refactored and maintained critical business intelligence reports used by machine learning scientists.
  • Prototyped a flexible, extensible ETL system to reduce a lot of boilerplate code in existing ETL scripts.
  • Created a web-based data dictionary to store metadata about tables in our warehouse. The front end was written in PHP with SQLite on the back-end to store the metadata.
  • Was considered a resident expert of our data warehouse.
  • Contributed to the on-boarding of two interns and two full-time employees.
  • Technologies Used: Perl, Pivotal Greenplum, PostgreSQL, Oracle, ActiveMQ, Python, PHP, Facebook Ads API, SVN

University of South Dakota

Assistant Professor - August 2004--May 2008

  • Six peer-reviewed mathematical publications.
  • Directed two undergraduate Honors Theses and a Master's Thesis in mathematics.
  • Sole organizer and director of a regional undergraduate mathematics conference.
  • Taught several courses, including College Algebra, Trigonometry, Calculus (I--III), Foundations of Mathematics, Matrix Theory, and Abstract Algebra.
  • Served and chaired several committees, including the Curriculum & Instruction committee.

Skills

Languages and Technologies

  • Programming Languages: Python, SQL, Bash, R, Java, Kotlin, Scala, Perl
  • Cloud Technologies:
    • AWS: Redshift, EMR, EC2, SageMaker, Lambda, Secrets Manager
    • Azure: Azure DevOps, Cosmos, Key Vault
    • Snowflake
  • Apache Spark, Apache Hive, Apache Hadoop, HDFS
  • Business Intelligence: Tableau, Microsoft Power BI, QlikView
  • Python libraries of note: PySpark, BlazingText, H3, Shapely, Pandas, NumPy, SciPy, scikit-learn, Requests, matplotlib, seaborn, plotly
  • Apache Airflow
  • IDEs/Text Editors Used: PyCharm, IntelliJ IDEA, Visual Studio Code, Eclipse
  • Data Formats: CSV, XSLX, JSON, GeoJSON, Parquet, XML
  • Docker
  • Version Control: Git, GitHub, GitLab, SVN, Assembla
  • Task Tracking and Documentation: JIRA, Azure Devops Boards, Pivotal Tracker, Confluence, Assembla
  • Operating Systems: Linux (Amazon Linux, openSUSE, Ubuntu, CentOS, RHEL), macOS, Windows, WSL, WSL2
  • APIs used: Salesforce, Zendesk, SurveyMonkey, Ramp, Aylien, 42matters, Infegy Social Radar API, Facebook Ads API

Other Skills

  • Mathematics
  • Python
  • Topological Data Analysis
  • Data mining
  • Data visualization
  • Implementing algorithms and ideas gleaned from academic publications

Education

North Dakota State University

Ph.D. Mathematics, May 2004

B.S. Mathematics, Dec 1999

Training Courses and Professional Development

  • AWS MLOps Training and Workshop, 2024
  • AWS Training from Amazon Web Services, 2018
  • Apache Cassandra training from Learning Tree International, 2017
  • Apache Spark training from Databricks, 2017
  • Hadoop and MapReduce Training from Hortonworks, 2015
  • Data Anonymization Training from Privacy Analytics, 2015
  • Greenplum User Training from Pivotal, 2014
  • Attended KDD 2014
  • QlikView Developer Training from Qlik, 2013
  • Noble Dialer Operations Training from Noble Systems, 2013
  • Java Training from Webucator, 2012
  • PostgreSQL Training from Webucator, 2010