Data Scientist

About this role

• ETL Management: Assist in designing and implementing ETL flows to consolidate data from various sources for analysis and modeling.

• Database Maintenance: Collaborate with developers to ensure data integrity and accessibility for business-critical reporting.

• Exploratory Data Analysis (EDA): Identify, investigate, and explain trends and patterns within complex datasets to uncover business opportunities.

• Model Development: Support the full lifecycle (research, build, validate, and test) of Machine Learning models, including clustering, classification, regression, and recommendation engines.

• Optimization: Continuously monitor and help improve existing algorithms to ensure they remain accurate and effective for business optimization.

• Cross-Functional Partnership: Work alongside Product Managers, Business Owners, and Developers to understand business needs and translate them into technical solutions.

• Data Storytelling: Break down complex technical concepts into clear, simple reports and visualizations for non-technical stakeholders.

• Global Support: Provide cross-country analytical support to ensure consistency in data standards and insights across the organization’s regional offices.

Who we’re looking for

• At least a Bachelor’s degree in Statistics, Mathematics, Computer Science
• Knowledge, Skills and Abilities
• related quantitative field
• • A strong foundational understanding of statistical concepts and a natural curiosity for discovering patterns within data.
• • High level of accuracy and thoroughness when cleaning and validating data to ensure "single source of truth" reporting.
• • Solid proficiency in SQL (ability to join tables, use aggregate functions, and write efficient queries).
• • Foundational knowledge of Python for data analysis (familiarity with libraries such as Pandas and Matplotlib/Seaborn).
• • Basic experience creating reports or dashboards in Power BI, Tableau, or similar tools to communicate data findings.
• • Exposure to or academic experience with cloud environments like AWS or GCP is a plus, but not required.
• • Ability to clearly explain your data findings and logic to team members and stakeholders.
• • A "quick learner" mentality with the ability to pivot between tasks and pick up new technical frameworks rapidly.
• • A team-oriented mindset with the integrity and work ethic to thrive in a fast-paced, evolving environment.
• • Highly motivated to take ownership of small projects and a proactive desire to be mentored and develop advanced data science skills.