Senior Data Scientist - Remote

Overview

The Data & Analytics department at Blip is responsible for empowering the company in generating knowledge, guiding data-driven decision-making, and driving innovation through data. It plays a crucial role in the evolution of Blip.

Our Data for Services area aims to create value for our clients through the implementation of high-value data services, focusing on applied diagnostics, statistical modeling, predictive and prescriptive analyses. We intentionally work to enhance customer satisfaction, strengthen the use of data from design on the platform, and promote hyper-personalized experiences.

As a Senior Data Scientist, we expect you to be a technical reference in data science and MLOps practices, working on the design and implementation of scalable analytical solutions, conducting advanced experiments, sharing knowledge, and keeping up with industry trends to ensure technical excellence and business impact.

In Short

• Lead advanced analytical studies using statistical methods and Data Science to identify hidden patterns.
• Translate complex business problems into rigorous analytical hypotheses and high-impact data-driven solutions.
• Design, develop, and operationalize cutting-edge predictive and prescriptive models.
• Ensure the robustness and sustainability of models in production applying MLOps best practices.
• Collaborate with Data Engineering teams and Product Managers to optimize data pipelines.
• Contribute to the evolution of analytical architecture and data governance.
• Lead experiments and proofs of concept in AI applied to business.
• Act as a technical mentor, disseminating knowledge and best practices in Data Science.
• Promote an analytical culture ensuring decisions are evidence-based.

Requirements

• Proficiency in Python for analysis and statistical modeling.
• Expertise in SQL and handling large data volumes.
• Solid experience with data science libraries (pandas, numpy, scikit-learn, statsmodels, PySpark).
• Experience with Spark and/or distributed processing.
• Knowledge in inferential statistics, hypothesis testing, and multivariate analysis.
• Proven experience with predictive modeling and performance evaluation of models.
• Strong data storytelling skills to translate complex technical insights.
• Experience in MLOps, including GIT for code versioning.
• Ability to translate business hypotheses into analytical solutions.
• Collaboration, curiosity, communication, and technical leadership skills.

Benefits

• Flexible working hours.
• Flexible work models: remote, hybrid, or in-person.
• No dress code.
• Home office support for setting up your workspace.
• Birthday day off.
• 5 paid days off per year for non-time-tracked positions.
• Meal or food allowance.
• Transportation allowance as needed.
• Access to wellness programs.
• Health insurance with national coverage.
• Psychological online support platform.
• Extended maternity and paternity leave.
• Support for children with disabilities.