Djalma Junior

Data Scientist

Talent

Kitchener, WaterlooMember since March 3, 2023

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About

Hardworking Data Scientist with experience in startups and consultancies, well adapted to a fast-paced environment and great commitment to the team, creating business insights, working with company strategy, synthesizing information, deploying models, and evaluating trends to enhance business KPIs which are my passion.

Experience

TC TRADERS CLUB LTDA

DATA SCIENTIST II (Corporative)

SP/ BRAZIL

NOV 21 – DEC 22

Developed a machine learning model to classify news genre with 92% precision, resulting in boosting in 13% the post speed of the news.

● Developed machine learning models to predict consumer behavior with 80% accuracy, resulting in a 5% increase in customer engagement.

● Developed a data visualization dashboard to track progress and performance metrics, allowing for real-time monitoring of key areas.

● Developed A/B testing on the website that led to a 5% increase in click-through rate in the recommended news tab.

Tools: BigQuery, GCP, K8s, Transformers, ElasticSearch, Docker, MLFlow, SQL, BERT, NLP, Python, Agile, Scrum, Jenkins.

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2DS DATA SCIENCE CONSULTANCY (merged with TC TRADERS CLUB in NOV 21)

DATA SCIENTIST (Consultant)

SP/ BRAZIL

JAN 21 – NOV 21

Developed a machine learning model to predict customer purchase propensity with a lift gain of 2.5, thus reducing the sales cost to 40%.

● Analyzed customer data and created a cluster to increase company revenue through personalized marketing campaigns for the most loyal customers, contributing 30% of the company's revenue.

● Created a machine learning model that increased the accuracy of predicting customer churn, saving the company annual retention costs.

Tools: SQL, Postgres, Python, AWS S3-EC2, PySpark, MLFlow, PowerBI, Machine Learning, ETL, Big Data, Hadoop.

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LIQUID CONSULTING

DATA ANALYST (Consultant)

SP/ BRAZIL

AUG 18 – SEP 20

Successfully created & implemented a data-driven approach to inventory management, reducing waste & increasing efficiency by 15% at the Nestle chocolate manufacturing plant in Brazil.

● Developed a data analysis process that provides plant management with real-time reports to monitor bottlenecks, resulting in increased production by 10% at the Nestle spice manufacturing plant in Chile.

● Utilized regression model to predict chain store sales forecast model for the next six weeks.

Tools: Spark, Python, SQL Server, Report Builder, Skelta, MES, DMO, Archestra, Rockwell, Intouch.