BI & Data Analytics Coordinator

Job Description:

• Build data visualisation and dashboard for the business
• Promote data-driven decision by aggregating and surfacing data across multiple platforms
• Ad-hoc analysis based on strategic direction of the business and deep dive into specific area
• Make recommendations based on historical data and predict trends
• Design, develop and implement statistical models, as well as interpret and present statistical outcomes to support the organisation's operations and execution of key business strategies
• Develop metrics that cut beyond surface-level and partner with engineering to ensure appropriate data capture
• Collaborate with stakeholders to build data analytics capabilities, conduct feasibility studies.
• Perform complex analysis on simulations on payments pipeline usage behavior
• Develop strategies, measure performance, and execute scenarios analysis.
• Transform data and other information sources into insights, facilitating the decision-making process.
• Prepare and participate in recurrent calls, business reviews, and workshops to support business.
• Establish relationships with different partners inside the company to optimize and enhance operation standards.
• Manage the data migrations and automatize routines

Requirements:

• Strong business acumen.
• Demonstrated ability to meet deadlines while managing multiple competing projects.
• Strong communication skills and advanced writing and speaking in English, and ability to synthesize analysis into insights.
• Basic understanding in descriptive statistics and familiar with inferential statistics.
• Experience with Python
• Experience in Data modeling/EDA (Exploratory Data Analysis)
• Good communications in English. Spanish intermediate level is a plus
• Degree holder in a business related field as long as there is a strong interest in data analysis;
• Excellent working knowledge with query language (SQL, NoSql, MSSQL, …)
• Experience working knowledge with data visualization (DataStudio, PowerBI, Tableau…)
• Experience working knowledge with data processing languages such as (Python, Go, Spark…)
• Working knowledge of data mining principles: predictive analytics, mapping, collecting data from multiple data systems on premises and cloud-based data sources
• Knowledge of analytical and statistical modelling techniques: hypothesis development, designing tests/experiments, analysing data, regression (multiple, logistic, log-linear), neural network, decision tree, variable selection, etc