data scientist

Overview

Who you'll be working for

What requirements you'll need to be eligible

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.

What you'll be doing on the job

• 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.

Consultant Contact