Djalma Junior

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.

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.

Fatec Sao Bernardo do Campo College 
Bachelor's degree in Industrial Automation
Data Science School
Storytelling with data
Data Science Project Production
Scrum, Agile Methodology
Business solving with CRISP-DM
SQL for BigQuery and Cloud SQL - Google
Statistics for data science and data analytics