Robert Manriquez, Developer in Los Angeles, CA, United States
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Robert Manriquez

Verified Expert  in Engineering

Data Visualization Developer

Los Angeles, CA, United States
Toptal Member Since
June 22, 2020

Robert is a data scientist with skills in engineering practices with data. He builds end-to-end data products using "full-stack" data science bringing ML, ETL, and BI/analytics reporting from prototype to production on cloud infrastructure. Robert works closely with clients and stakeholders to translate business needs into solutions with Python, SQL, Spark, AWS, and GCP tools. He is passionate about education and teaching data science, machine learning, and statistics topics.


Kubernetes, Docker, JavaScript, CSS, HTML, Flask, Looker...
Emeritus Institute
Jupyter, Scikit-learn, SQL, Python
Return Path
Amazon Web Services (AWS), Apache Airflow, Jenkins, Git, TensorFlow...




Preferred Environment

Jupyter, PyCharm, G Suite, Slack, MacOS

The most amazing...

...project I've worked on was a terabyte-scale AI platform serving 200+ customers daily.

Work Experience

Data Engineer

2019 - 2020
  • Solved client business problems on $2 million worth of contracts using data models, warehousing/ETL, and data analysis.
  • Designed and deployed ETL pipelines to collect, ingest, store, and retrieve data effectively.
  • Built, designed, maintained back-end cloud infrastructure, and containerized applications (GCP, Docker, and Kubernetes) .
  • Quickly architected solutions closing out three major projects using Agile methods and software engineering best practices.
  • Developed custom web applications delivering live performance analytics directly to executive and marketing teams.
  • Implemented front-end frameworks (Flask/HTML/CSS/JavaScript) and business intelligence reporting (Looker).
Technologies: Kubernetes, Docker, JavaScript, CSS, HTML, Flask, Looker, Google Cloud Platform (GCP), MySQL, PostgreSQL, Python

Data Science Course Leader

2018 - 2019
Emeritus Institute
  • Taught applied data science to four cohorts consisting of over 200 students, responsible for retaining over $200,000 in tuition.
  • Delivered five custom webinars on machine learning, statistics, and mathematics tailored according to student needs.
  • Ensured student understanding of analytics methodologies, hypothesis testing, computer science, programming, and SQL.
Technologies: Jupyter, Scikit-learn, SQL, Python

Data Scientist II

2018 - 2019
Return Path
  • Improved and maintained dynamic optimization AI models enhancing email deliverability to over 300 customers daily.
  • Quantified performance metrics identifying >$150,000 in Snowflake costs savings and 2x increase data preprocessing speed.
  • Developed terabyte-scale data ETL, improving model training job success rate by 50% (Snowflake, Spark, Airflow, AWS).
  • Guided business decisions and strategy directly to project management and leadership closing out six quarterly objectives.
  • Collaborated with senior data scientists, engineers, and Agile methodologies for rapid iteration, validation, and evaluation.
Technologies: Amazon Web Services (AWS), Apache Airflow, Jenkins, Git, TensorFlow, Scikit-learn, Jupyter, Snowflake, SQL, Scala, Spark, Python

Data Science Instructional Associate

2018 - 2018
General Assembly
  • Supported 75+ students in teaching Python, Data Science, Git, and machine learning fundamentals.
  • Led student discussions ensuring student understanding via 1-on-1 sessions.
  • Identified difficult topics and creating additional course content for struggling students.
  • Translated difficult technical topics into accessible and meaningful terms.
  • Analyzed and troubleshot student coding assignments and projects.
Technologies: Jupyter, Scikit-learn, Git, SQL, Python

Data Scientist

2018 - 2018
  • Improved performance of deal prediction model by 20%, generating $50,000+ in additional sales in three months.
  • Developed asset clustering and segmentation models to automate sales prospecting, saving 10 hours/week in labor.
  • Revamped legacy ETL into Databricks/Azure cloud, and built dashboards directly serving executive and marketing teams.
  • Prototyped, improved, and managed supervised/unsupervised machine learning models in production (Python, R, SparkML).
Technologies: Scikit-learn, Databricks, Azure, R, Spark, Python

R&D Engineer II

2014 - 2017
Next Energy Technologies
  • Achieved major contributions to research completing two NSF milestones and securing $7 million in Series B funding.
  • Guided research and strategic decisions to leadership via data analysis, technical presentations, and data story-telling.
  • Optimized production and research protocols, implemented best practices for analyzing data.
  • Managed four junior engineers and interns; assumed responsibility for maintaining lab resources.
Technologies: Mathematica, LabVIEW, MATLAB, Python

Email Read Rates
Using a sample of email event data, I created an approach and several models to predict read rates of emails based on events and subscriber engagement. This consisted of creating a modular, version-controlled codebase using Python and Scikit-Learn. Analysis and modeling were described and quantified in a concise report.


Data Analysis, Research, Machine Learning, Data Visualization, Data Engineering


Python 3, SQL, Python, Scala, R, HTML, CSS, JavaScript, Snowflake


Spark, Flask


TensorFlow, Scikit-learn


Git, Looker, Tableau, Slack, G Suite, PyCharm, Jupyter, Jenkins, Apache Airflow, MATLAB, LabVIEW, Mathematica


ETL, Data Science


Google Cloud Platform (GCP), Docker, Kubernetes, Amazon Web Services (AWS), MacOS, Azure, Databricks


PostgreSQL, MySQL

2013 - 2014

Master of Science Degree in Materials Science and Engineering

University of California, Santa Barbara - Santa Barbara, CA

2010 - 2013

Bachelor of Science Degree in Chemistry

University of California, Santa Barbara - Santa Barbara, CA