Hiro Shioi, Developer in Pleasanton, CA, United States
Hiro is available for hire
Hire Hiro

Hiro Shioi

Verified Expert  in Engineering

Bio

Hiro is a customer-facing data scientist. He excels at very high-level data science problems (ideation, road mapping, ROI estimation, solution and data architecting) to hands-on execution (data cleansing, feature engineering, modeling, operationalization). At General Electric, Hiro led a million-dollar digital transformation advisory project and developed 15 data science products across the healthcare, mining, telecommunications, manufacturing, transportation, power, and financial industries.

Portfolio

dotData Inc.
Python, PySpark, Tableau, Microsoft Power BI, SQL, Snowflake, Databricks...
General Electric
Python, Anomaly Detection, PySpark, Machine Learning, Data Science...

Experience

Jupyter Notebook - 7 yearsPython - 7 yearsMachine Learning - 7 yearsClient Presentations - 5 yearsSQL - 4 yearsTableau - 4 yearsPySpark - 2 yearsAmazon Web Services (AWS) - 2 years

Availability

Part-time

Preferred Environment

Python, Jupyter Notebook, Amazon Web Services (AWS), Azure, Data Science, Data Analysis, Pandas, Scikit-learn, Amazon S3 (AWS S3), Amazon EC2, APIs

The most amazing...

...customer-focused and executed business outcome I delivered was worth $8 million to the client and completed within 60 days.

Work Experience

Senior Data Scientist

2020 - PRESENT
dotData Inc.
  • Served as a single customer-facing data scientist, closing the deal for the happiest customer by validating an $8 million revenue increase per month and operationalizing the ML model within 60 days.
  • Developed automated data science (automated feature engineering and AutoML) use cases for businesses across industries, e.g., eCommerce, manufacturing, retail, and finance.
  • Directed engineers to improve the products and add-on features as a product manager by leveraging customer-facing knowledge.
Technologies: Python, PySpark, Tableau, Microsoft Power BI, SQL, Snowflake, Databricks, Amazon Web Services (AWS), Azure, Data Science, Data Analysis, Pandas, Scikit-learn, Amazon S3 (AWS S3), Amazon EC2, APIs

Senior Data Scientist

2016 - 2020
General Electric
  • Developed 15 data science products and solutions for customers across verticals such as healthcare, mining, telecommunications, manufacturing, transportation, power, and the financial industries.
  • Led the million-dollar contract for a digital transformation advisory project of a financial institution.
  • Developed anomaly detection models using machine learning and physics-based models applying signal processing based on 14 time-series sensors in Python.
  • Delivered an analytic report for millions of time-series log and service data records.
Technologies: Python, Anomaly Detection, PySpark, Machine Learning, Data Science, Data Analysis, Pandas, Scikit-learn, APIs

Flask App for Anomaly Detection Using User Session Logs

I developed a RESTful API service using Flask (Python framework) that consumed user logs to detect unusual behavior using machine learning techniques during a hackathon. In this application, I developed the parsing and preprocessing script, machine learning models (logistic regression, decision tree, XGBoost, etc.), and the training and prediction pipeline.
2011 - 2014

Master's Degree in Aerospace Engineering

The University of Tokyo - Tokyo, Japan

2012 - 2013

Research Towards a Degree in Computer Science

ETH Zurich (Swiss Federal Institute of Technology in Zurich) - Zurich, Switzerland

2007 - 2011

Bachelor's Degree in Aerospace Engineering

The University of Tokyo - Tokyo, Japan

Libraries/APIs

Pandas, Scikit-learn, PySpark, REST APIs, XGBoost

Tools

Tableau, Microsoft Power BI

Languages

Python, SQL, Snowflake

Paradigms

Anomaly Detection

Platforms

Jupyter Notebook, Amazon EC2, Databricks, Amazon Web Services (AWS), Azure

Storage

Amazon S3 (AWS S3)

Frameworks

Flask

Other

Machine Learning, Data Science, Data Analysis, APIs, Client Presentations, Object Detection

Collaboration That Works

How to Work with Toptal

Toptal matches you directly with global industry experts from our network in hours—not weeks or months.

1

Share your needs

Discuss your requirements and refine your scope in a call with a Toptal domain expert.
2

Choose your talent

Get a short list of expertly matched talent within 24 hours to review, interview, and choose from.
3

Start your risk-free talent trial

Work with your chosen talent on a trial basis for up to two weeks. Pay only if you decide to hire them.

Top talent is in high demand.

Start hiring