Daniel Alarcon Email & Phone Number

Cincinnati, Ohio, US

• Led a team of 10+ engineers in developing Proof of Concepts for Machine Learning projects.
• Managed a Kubernetes cluster on Azure cloud, ensuring high availability and scalability.
• Architected a system for the automatic creation, deployment, and maintenance of AI-enabled applications with reusable templates for Data Scientists.
• Integrated CI/CD pipelines for unit testing, linting, and Docker image deployment.
• Developed and orchestrated machine learning pipelines to streamline the deployment and monitoring of models in production.
• Collaborated with cross-functional teams to ensure seamless integration of AI solutions into business processes.

New York City, New York, US

• Created store transactions streaming app, feeding records through to a Power BI Dataset & UI for stakeholders to view sales statistics in real-time (Scala, Spark, Kafka, Power BI).
• Implemented a scalable end-to-end Machine Learning pipeline for Product Markdowns, including scheduled data processing, model training, and predictions accessible through an on-premises custom UI. Certain brands were.
• Migrated a sales extract process for Marketing Team and an Auto Replenishment system for online product forecasts from SQL legacy system into modern cloud-based Spark Application (Scala, Airflow, Spark, Databricks).
• Updates and monitors batch ETL processes for Foot Locker's Data Analytics Platform, which transfer various data sources into our centralized Azure Data Lake. This includes various bug fixes, backfills, and schema.
• Mentors, demonstrates, and presents to team members on best practices for code reuse, scalability, readability, memory management, and speed in 1:1's and bi-weekly sprint reviews.

• Lead the organization's data machine learning initiatives through the implementation of end-to-end machine learning pipelines & data analysis Jupyter notebooks.
• Created a product recommendation engine for the bank’s internal ultilities, processing over 200M+ transaction records to generate next best product recommendations for current banking clients (k-means clustering.
• Modeled client behavior to predict customer attrition in order to increase customer retention by 5% (XGBoost, Azure Data Factory, Azure Databricks).
• Designed an end-to-end PoC CD loan decisioning pipeline within the bank, deploying an internal ML API which achieved 98% precision on credit applications the model had never seen before (Python, XGBoost, BigQuery.
• Developed ETL pipelines for internal/on-premise use in BI reporting and for data analysis (SQL, Hadoop, Spark, Python, Azure Data Factory, Azure Data Bricks).
• Created user interfaces to display machine learning model results in real-time (React, TypeScript, Microsoft SQL Server)Skills Utilized:Google CloudAzure.

• Investigate the mental representations that underlie our conception of social groups (including stereotypes).
• Built and designed machine learning models using R and the glmnet package to explore how individuals think about different social groups, including k-means clustering and logistic regression.
• Present research findings in weekly meetings with Principal Investigator, Dr. Andrei Cimpian, and Postdoctoral researcher, Ryan Lei, to explain findings and develop new analysis strategies.

San Francisco, California, US

• Determined the database structure, the parameters accepted by REST APIs, and the returned response from APIs for use by main website.
• Used Natural Language Processing (NLP) techniques to create features for Brand Detector model
• Built and designed deployable machine learning models using Python, Tensorflow, and Docker Flask Apps, providing REST APIs load balanced and managed through AWS Elastic Beanstalk.
• Designed and implemented data migrations, transformations, and scripting to integrate machine learning model predictions into website infrastructure.

New York, NY, US

• Built and designed machine learning models using R and the glmnet package to explore the effects of methylation on in vitro transcription factor (TF) binding.
• Trained binary logistic regression models using un-methylated and methylated high-throughput SELEX data for each TF, separating high-affinity from low-affinity binding probes.
• Presented research findings in a poster session with research members of Memorial Sloan Kettering.

New York, US

• Manage multiple time-sensitive projects for diverse stakeholders, including Employer Partners, NYU Staff, and various charity organizations
• Assist with equipment/computer and room set-ups and breakdowns
• Transport promotional and technical materials to event locations on-campus
• Added support for general office duties and special projects as needed.

New York, NY, US

I worked in a team of interns assisting the DNA Unit in developing and operating open-sourced software for the analysis of complex DNA mixtures left at crime scenes in real case work. I analyzed large data sets relating to DNA analysis and helped compile exhibits for legal motions and scientific papers.

• Fostered long lasting relationships between the alumni and the university by building rapport.
• Raised funds for scholarships and student programming by contacting NYU students, parents, and alumni through the company’s computer program.
• Successfully learned from my experiences and work to build calling skills.

• Engaged with clients in English or Spanish, ensuring a welcome environment in the restaurant
• Answered calls and created reservations for potential customers
• Monitored inventory of all products in the restaurant, logging any shortages for re-ordering.
• Helped the assistant chef assemble the orders to take to customers when requested.