• Data Analysis:

  • Data source analysis and validation

  • Utilize statistical analysis, data visualization, and data mining techniques to identify trends, patterns, and correlations in the data

  • Generate actionable insights and provide data-driven recommendations to support business strategies

• Reporting and Visualization:

  • Design and create comprehensive reports and dashboards to communicate findings effectively to both technical and non-technical stakeholders

  • Collaborate with cross-functional teams to understand reporting requirements and deliver meaningful visualizations

• Predictive Modeling:

  • Develop and implement predictive models using machine learning techniques to forecast future trends and outcomes

  • Continuously improve and refine models based on feedback and changing business needs

• Collaboration:

  • Collaborate with various departments to understand their data needs and provide support in leveraging data for decision-making

  • Act as a key liaison between technical and non-technical teams, fostering a data-driven culture

• CRM Management

  • Act as a point-of-resource to other departments and make sure all data coming from various departments (Finance, Marketing, Sales, Customer Experience) are smoothly connected and integrated in our systems

  • Create training materials and troubleshooting documents

• Data Collection and Cleaning:

  • Gather and clean large datasets from various sources to ensure data accuracy and integrity

  • Develop and implement processes for data validation and cleansing to maintain high-quality datasets

Technical Skills:

• Proficiency in statistical analysis, regression, forecasting, and other advanced data analysis techniques

• Knowledge of programming languages such as Python or R for data manipulation, analysis, and visualization

• Ability to create insightful, interactive visualizations using tools like Tableau, Power BI, or programming libraries (e.g., Matplotlib, Seaborn, ggplot2)

• Experience with database technologies (SQL, NoSQL) for querying, extracting, and handling data from various sources

• Skills in cleaning, transforming, and preparing data for analysis

• Understanding of machine learning algorithms for predictive analytics and the 

Business Acumen:

• Ability to translate business problems into analytical questions and provide data-driven insights and solutions.

• Understanding of the startup’s industry, market trends, and competitive landscape to inform analysis and recommendations.

• Familiarity with the product/service to analyze customer behavior, product performance, and identify growth opportunities.

• Capability to think strategically about the long-term implications of data findings on business goals and strategy.

Soft Skills:

• Excellent communication skills to articulate complex data insights clearly and effectively to stakeholders.

• Collaboration with different teams (e.g., product, marketing, engineering) to implement data-driven strategies and improvements.

• Flexibility to adapt to the dynamic startup environment, where priorities and projects can change rapidly.

• Proactivity in identifying opportunities for data analysis that can drive value for the business.

• Critical thinking to question assumptions, validate data sources, and evaluate analysis results.

• Project management skills to manage analytics projects from conception to completion, ensuring timely delivery of insights.

• Ability to implement models for informed decision-making