Data Scientist

                Resumen de descripción de puesto
Analyze large amounts of raw data to find patterns that help improve our business decisions. We will rely on building data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math, and statistics. Critical thinking and problem-solving skills are essential to interpreting data. We also want to see a passion for machine learning and research.
The goal will be to help us analyze trends to make better decisions.

Business Acumen: Using your business acumen and key insights, you proactively explore new areas of opportunities to drive Rappi's value and growth goals forward and coordinate with the key stakeholders to prioritize and lead the changes to production. You proactively monitor existing metrics, develop, and propose new metrics, and work across the organization to make actionable intelligence available to business stakeholders.
Strategic Analytics and Insights: With a deep understanding of business drivers and an innate grasp of the key business metrics, you pro-actively interact with the stakeholders within the business teams and drive customer-centric changes through data-driven deep-dives, insights at scale, and analytical exercises (preliminary data analysis, deep-dives using segmentations/models, financial analysis and recommendations).
Customer Centricity: Focusing on the incrementality and the value-creation in everything you do, you drive strategic insights on customer behavior (customer acquisition, marketing investment analysis and optimization, engagement RFM, retention, product-mix, sales, etc.), customer needs (pricing, product, convenience, experience, etc.), and existing/new propositions (loyalty programs, sales campaigns, discounted offers, etc.) across various membership types and marketing channels for Rappi customers.
Execution: Ability to communicate insights and identify new areas of opportunity that will drive Rappi's value and growth goals forward; coordinate with the stakeholders to prioritize and lead the changes to production. Establish strong working relationships at all organizational levels across different functional teams.

- Understand business objectives to provide actionable insights.
- Collaborate with cross-functional teams to tackle real-world challenges.
- Collect, clean, and analyze data from diverse sources.
- Explore large datasets and perform statistical analysis.
- Create data visualizations to drive understanding.
- Develop and manage Airflow data pipelines to ensure scalable and reliable feature ingestion.
- Design data services and APIs.
- Deploy and maintain machine learning MS services in production environments.
- Engage with clients and stakeholders in meaningful discussions.
- Utilizing machine learning and statistical tools to select features, develop and optimize models, and extract business insights
- Carrying out preprocessing of structured and unstructured data
- Enhancing data collection procedures to include all relevant information for developing analytic systems
- Processing, cleansing, and validating the integrity of data to be used for analysis
- Analyzing large amounts of information to find patterns and solutions
- Developing prediction systems and machine learning algorithms
- Presenting results in a clear manner
- Propose solutions and strategies to tackle business challenges