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Bernardo – Python, Data Science, Machine learning, experts in Lemon.io

Bernardo

From Brazil

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Data ScientistSenior
Machine Learning EngineerSenior
Hire developer
8 years of commercial experience
Asset management
Business intelligence
Cryptocurrency
Data analytics
Fintech
Healthcare
Insurance
NFT
Productivity
Project management
Social media
Trade
AI software
Communication tools
Platforms
Lemon.io stats
1
projects done
1211
hours worked
Open
to new offers

Bernardo – Python, Data Science, Machine learning

Bernardo, a Senior Data Scientist/Machine Learning Engineer, brings over 15 years of industry experience to the table. Over the last 7 years, he has mastered his data science and machine learning skills. With a diverse background that includes product ownership roles, Bernardo has seamlessly navigated between large corporations and startups throughout his career.

Main technologies
Python
7 years
Data Science
7 years
Machine learning
7 years
Docker
4 years
Scikit-learn
7 years
SQL
7 years
NumPy
7 years
SciPy
7 years
MLOps
5 years
ETL
4 years
Additional skills
Pandas
Django
MySQL
Redis
AWS
Apache Spark
Kubernetes
Blockchain
Microsoft Azure
Matplotlib
Apache Airflow
PySpark
Amazon RDS
Heroku
BigQuery
R
Nginx
Microsoft Power BI
Big Data
AWS CloudFormation
Tensorflow
PyTorch
Rewards and achievements
Big tech veteran
Ready to start
ASAP
Direct hire
Potentially possible

Experience Highlights

Data Scientist
Dec 2022 - Aug 20237 months
Project Overview

A Canadian startup that delivers digital asset analytics powered by AI. Focused on the promising NFT market, it allows customers to measure the fair market value of digital assets accurately.

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Responsibilities:
  • Was responsible for technical aspects of the core NFT price prediction engine, including research, development, deployment, monitoring, and maintenance in production
  • Developed machine learning models using time series techniques to support EVM and non-EVM compatible blockchains; ERC-1155 and ERC-721 tokens in Ethereum
  • Expanded the machine learning system, delivered over a Rest API, to support over 1000 NFT collections and output prices in any token designated by the user, increasing product attractiveness
  • Developed a daily automated model performance verification system to update models with low performance in out-of-sample data, successfully safeguarding the user experience
  • Integrated leading blockchain data providers via Rest and Graphql APIs using synchronous, paginated, and asynchronous data retrieval processes, with data integrity verified by validation rules
Project Tech stack:
Python
Scikit-learn
Pandas
NumPy
SciPy
Celery
Django REST
Docker
Kubernetes
Amazon EC2
Amazon ECS
PostgreSQL
Redis
Blockchain
AWS
Machine learning
Data Science
Data Scientist
Apr 2022 - Jul 20223 months
Project Overview

An independent asset management firm in the US market with over $150 MM AUM. The project was a machine learning system to generate market-beating stock portfolios and inform the portfolio manager's decisions. This was a contract project through Virtualmind, working daily side-by-side with the investment portfolio manager.

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Responsibilities:
  • Developed a machine learning system for stock portfolio building incorporating innovative financial indicators
  • Increased portfolio performance using parameter optimization to achieve up to 30% lift in returns
  • Delivered a cloud data product to automate a training and prediction pipeline of US stock market historical data, generating portfolios before market open time
  • Developed a model performance monitoring system using a cloud machine learning model logging tool
Project Tech stack:
Python
Scikit-learn
NumPy
Pandas
SciPy
Matplotlib
Machine learning
Microsoft Azure
Data Science
Data Scientist
Oct 2021 - Mar 20224 months
Project Overview

The product gives managers (and team members) the capabilities they need to measure team engagement and accelerate team performance. The project was to build core product features from scratch as a web app and its integrations in team comms platforms.

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Responsibilities:
  • Was responsible for research and development of statistical models leveraging behavior science to measure human factors in remote team management
  • Built the foundation of the core feature to distribute hundreds of questionnaires with randomized questions delivered in batches of similar statistical properties
  • Collaborated with product research team and leadership to translate value-generating ideas into data models to support new features and business goals
  • Developed a data API for end user-facing product dashboards using analytical queries achieving sub-50ms API response time on the 95th percentile with caching
Project Tech stack:
Python
Scikit-learn
Pandas
NumPy
SciPy
Data Science
PostgreSQL
Django REST
Celery
Docker
Redis
Data Engineer
Mar 2021 - Sep 20215 months
Project Overview

As part of Company's Business Intelligence team, his role was to develop and maintain data processing pipelines and datasets crucial to business management.

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Responsibilities:
  • Optimized long-running Apache Spark, Hive, and Presto distributed data cluster jobs and Apache Airflow DAGs, achieving efficiency gains in resource usage and reducing cloud costs
  • Maintained datasets updated daily with D+0, D+1, and D+2 SLA with giga and terabyte scales
  • Collaborated with product analysts to translate business reporting requirements following data availability and data lineage assessments
  • Developed documentation of existing and new datasets and data pipelines, supporting the work of a team of 20 engineers
Project Tech stack:
Python
Amazon EC2
Apache Spark
PySpark
Hive
Amazon S3
Apache Airflow
SQL
Big Data
Data Warehouse
Data analysis
Data Scientist
Jul 2016 - Feb 20214 years 7 months
Project Overview

Brazil's first life insurance startup dedicated to people with chronic conditions. As a founding team member, he could participate in all stages of a growing startup.

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Responsibilities:
  • Was responsible for technical research, development, deployment, and maintenance of core life insurance risk scoring system, which calculated the risk score of thousands of recurring payment customers along their subscription and renewal journeys; the system also supported all online price quotes on the platform
  • Developed a statistical model from a spreadsheet into a productized system that could output a risk score via a Rest API in collaboration with an international actuarial team
  • Developed a machine learning system to classify the quality of online leads. Leads were classified into high, medium and low quality and distributed to the commercial team to maximize team efficiency
  • Developed a mathematical model for lead conversion over time, offering deeper insights into commercial team performance and company revenue forecast
  • Developed and delivered a complete business intelligence system, including automated and man-in-the-loop daily ETL processes, along with data visualization dashboards for leadership, business development, marketing, and product stakeholders
  • Created and led the Analytics team, responsible for risk scoring and business reporting to internal stakeholders and board members
  • Supported early-stage lean startup efforts offering data-based evidence and analyses to inform product hypotheses validation and achieve product-market fit
Project Tech stack:
Python
Scikit-learn
Pandas
SciPy
Data Science
Machine learning
Heroku
DigitalOcean
MySQL
Docker
Flask
AWS Lambda
Amazon EC2
BigQuery
MongoDB
Amazon RDS
Nginx
Microsoft Power BI
R
Data Warehouse
Data analysis

Education

2023
Mathematics
Bachelor's

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