Solutions Architect
2020 - PRESENTDatabricks- Designed solutions for customers on top of the Databricks platform.
- Provided technical support to the sales team, delivered presentations and workshops to customers to close business.
- Assisted with deployments of the platform in a multi-cloud environment (AWS/Azure).
Technologies: Amazon Web Services (AWS), SparkBig Data and AI Tech Lead
2019 - 2020Paradigma Digital- Consulted across several industries, including banking (consumer finance), media, and utilities.
- Provided project management within the data science space, leading teams of up to five individual contributors.
- Hired and screened technical staff, including data scientists, data engineers, big data architects, and data governance consultants.
Technologies: Amazon Web Services (AWS), Scikit-learn, PythonData Science Manager
2016 - 2019Stratio Big Data- Segmented products in sales levels using unsupervised machine learning for personalized treatment when building predictive models.
- Overhauled the architecture to improve the scalability of the system. Performing 20 million daily regressions within a demand forecasting problem in a distributed cluster in less than 8 hours.
- Led a data science team of five engineers within a demand forecasting project in retail.
- Developed new business development and analytics (presales). Held a 30% conversion rate from proposal to contract in data science projects over my tenure in presales.
- Assisted deals in retail, media, education, banking, marketing, and utility industry sectors.
Technologies: Scikit-learn, Python, Hue, Impala, Apache Hive, Kudu, HDFS, Spark, ClouderaChief Data Scientist
2014 - 2016Jobandtalent- Designed and implemented a matching algorithm for job offer recommendations based on conditional relevance models by analyzing career paths in resume databases.
- Doubled the conversion rate of the recommender pipeline with the algorithm, resulting in an equivalent increase in the number of monthly job applications.
- Prototyped a system for improving customer segmentation in email marketing in order to increase sales of online courses, with the idea of targeting users at the micro-level as opposed to targeting them by area of expertise.
- Created a distributed system on top of Elastic MapReduce for tuning machine learning hyperparameters, accelerating run time of grid searches by 50x in an information retrieval application.
- Proactively wrote a tool to automate dashboard generation and trained the BI team on its usage, shaving weekly hours of routine work from their schedule.
- Delivered lectures to co-workers on Information Retrieval concepts.
- Authored feature description specifications for several modules, defining the long term vision of the recommendation algorithm.
- Screened machine learning engineers in hiring processes conducting knowledge assessments within area of expertise.
Technologies: Discriminant Analysis (LDA), Topic Modeling, Amazon S3 (AWS S3), Redshift, Cloud Storage, BigQuery, R, PHP, Java, Redis, Apache Lucene, Hadoop