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ProAssets LLC

CVM Data Scientist

Certificates : Evidencia de estudios (Mandatory)

Division/Department : B2C

Skills : Interpersonal skills, Strategic planning, Problem solving, Flexibility, Decision making, Project management, Persuasion skills, Goal orientation, Leadership, Judgement, Stress management, Attention to detail, Customer satisfaction, Initiative, Work ethic, Planning, Communication, Multitasking, Teamwork, Participative leadership

Experience : 2 Years

Reports to :

Shift type : FullTime   |  Salary type : Exempt

  

1 month ago

Date : 02/02/2026

Job Description :

Essential Duties and Responsibilities:

  • Analyze large and complex telecom customer and network-related datasets to identify usage patterns, trends, and business opportunities
  • Develop and implement algorithms for customer segmentation, churn prediction, and behavioral analysis
  • Write efficient and complex SQL queries to extract, transform, and analyze data from high-volume telecom data warehouses
  • Build and validate statistical and machine learning models to support initiatives such as churn reduction, ARPU optimization, and customer lifetime value analysis
  • Collaborate with marketing, network, and product teams to translate analytical insights into actionable recommendations
  • Create dashboards, reports, and visualizations to communicate insights to technical and non-technical stakeholders
  • Ensure data quality, consistency, and governance across multiple telecom data sources (e.g., billing, CRM, network usage)
  • Continuously improve analytical models and methodologies to adapt to evolving customer behavior and market conditions
  • Other functions that may be assigned. 

Education and/or Experience:

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field 

2-5 years of progressive in strategy roles, product management, and customer value optimization.

Other Qualifications:

  • Fully bilingual
  • Experience in data analysis, business intelligence, or similar analytical roles.
  • Strong proficiency in SQL for querying, aggregating, and optimizing large-scale datasets.
  • Solid understanding of algorithms, data structures, and analytical techniques.
  • Experience with telecom customer analytics, subscriber behavior analysis, or churn modeling.
  • Proficiency in Python or R for data analysis and modeling.
  • Strong knowledge of statistical modeling and machine learning concepts
  • Ability to translate telecom business challenges into analytical solutions.
  • Strong problem-solving and communication skills.
  • Proficiency in data analysis tools such as SQL and Python, as well as visualization platforms like Tableau or Power BI.

EEOC