Data Scientist

Job Description:

Job Title: Data Scientist / Data Engineer - Customer Churn Analysis

Location: LATAM (Preferably Brazil - Remote)

Job Overview:

We are seeking a highly skilled Data Scientist/Data Engineer with 6–7+ years of experience to join our team, focusing on customer churn analysis. This role will leverage advanced analytics, machine learning, and data engineering techniques to understand customer behavior, identify churn risks, and develop actionable insights to improve customer retention. The ideal candidate will have a strong background in both data science and engineering, with expertise in predictive modeling and handling large-scale datasets.

Key Responsibilities:

• Customer Churn Analysis: Develop and implement predictive models to identify customers at risk of churning and recommend data-driven strategies for retention.
• Data Engineering: Design, build, and maintain data pipelines to collect, clean, and integrate data from multiple sources for analysis and modeling.
• Exploratory Data Analysis (EDA): Perform detailed analysis to uncover insights and trends in customer behavior, churn rates, and retention patterns.
• Machine Learning Models: Build and optimize machine learning models using tools like Python, R, or similar frameworks to predict customer churn.
• Stakeholder Collaboration: Work closely with marketing, sales, and customer service teams to align strategies based on analytical insights.
• Performance Monitoring: Develop dashboards and visualizations to track model performance and provide actionable insights using tools like Tableau, Power BI, or Looker.
• Documentation & Reporting: Document methodologies, processes, and insights clearly for technical and non-technical stakeholders.

Qualifications:

• Location: LATAM-based candidates are preferred, with a strong preference for candidates in Brazil.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
• Experience:
• 6–7+ years of combined experience in data science and data engineering.
• Proven track record in customer churn analysis and predictive modeling.
• Technical Skills:
• Proficiency in Python, R, or similar programming languages for data analysis and machine learning.
• Strong SQL skills for data extraction and manipulation.
• Experience with big data technologies such as Spark, Hadoop, or Kafka.
• Knowledge of cloud platforms (AWS, GCP, or Azure) and data storage solutions.
• Familiarity with data pipeline tools (e.g., Apache Airflow, Talend).
• Experience with visualization tools like Tableau, Power BI, or Looker.
• Soft Skills:
• Strong problem-solving and analytical thinking skills.
• Excellent communication and storytelling abilities to explain complex analyses to non-technical audiences.
• Ability to work collaboratively with cross-functional teams.

Preferred Qualifications:

• Knowledge of customer lifecycle management and customer segmentation strategies.
• Experience working in industries with high churn rates, such as telecommunications, e-commerce, or SaaS.
• Familiarity with advanced analytics techniques like time-series analysis and survival analysis.