Senior Data Analyst

About the role:

We are looking for a Senior Data Analyst to organize, analyze, and interpret information relevant to epidemiological surveillance. You will be part of a multidisciplinary team and work with public and private databases subject to delays, duplicates, incomplete fields, structural changes, and definitional differences.

We are looking for someone able to turn surveillance questions into analyses that can be reviewed and reproduced. As important as reaching an answer is explaining the limitations of the data and what they do not allow us to conclude. The leadership will be technical, involving methodological decisions, review, mentoring, and coordination of deliverables; the role does not involve formal people management. This is an applied analytics position; developing machine learning models is not part of the essential scope.

Responsibilities:

• Translate epidemiological surveillance and health management questions into clear and verifiable analysis plans;
• Develop and maintain transformations and analyses in SQL and in Python or R, with version control, testing, and documentation;
• Define indicators and document their formulas, sources, breakdowns, inclusion and exclusion criteria, and usage limitations;
• Assess data quality in terms of completeness, uniqueness, consistency, domain, timeliness, and source stability;
• Investigate discrepancies until their origin is identified, document conclusions, and verify corrections made;
• Produce dashboards, reports, tables, and visualizations appropriate to the audience and the decisions they should support;
• Analyze rates, time series, and territorial breakdowns, communicating uncertainties and avoiding interpretations not supported by the data;
• Maintain data dictionaries, methodological notes, and materials that allow results to be reproduced and reviewed;
• Apply risk-proportional controls in the handling of personal and sensitive data, in compliance with LGPD and applicable ethical standards;
• Work in partnership with epidemiologists, scientists, product, design, technology teams, and institutions responsible for the sources.

Requirements:

• Strong experience with SQL for data analysis and transformation, including complex queries and performance diagnostics;
• Strong experience with at least one analysis language, such as Python or R;
• Applied knowledge of statistics, including rates, time series, missing data, biases, and communication of uncertainty;
• Experience with data subject to quality issues, schema changes, and definitional differences;
• Experience with reproducible analyses, peer review, Git, and method documentation;
• Experience building dashboards, reports, or other analytical products used by different audiences;
• Ability to distinguish association from causality and to clearly explain what the data do or do not allow us to conclude;
• Knowledge of best practices in handling personal and sensitive data;
• Ability to make and communicate methodological decisions and support the work of others;
• Ability to read documentation and technical literature in English;
• Interest in applying data analytics to public health. Prior experience in the health sector is not required.

Preferred qualifications:

• Education or experience in epidemiology, public health, biostatistics, or health surveillance;
• Experience with Brazilian databases such as SINAN, SIVEP-Gripe, SIM, SINASC, e-SUS, GAL/LACEN, or other DATASUS sources;
• Experience with dbt, Prefect, Airflow, DuckDB, ClickHouse, BigQuery, or equivalent tools;
• Experience with surveillance methods, such as endemic channel, exponentially weighted moving average (EWMA), or nowcasting;
• Experience with geoprocessing and IBGE territorial grids.

Behavioral competencies:

• Ethical and respectful professional conduct, with courtesy in relationships, respect for diversity, and care with confidential information;
• Ability to work in multidisciplinary teams, collaborating on deliverables, valuing different perspectives, and recognizing others' contributions;
• Willingness to share knowledge, document learnings, and support colleagues' development, reducing dependence on individual knowledge;
• Clear and respectful communication, with active listening to understand needs, clarify doubts, and align expectations;
• Openness to give and receive constructive feedback and handle disagreements through dialogue, with a focus on problem-solving;
• Organization and responsibility with deadlines and commitments, communicating difficulties and risks in advance and seeking support when necessary;
• Willingness to learn continuously and adapt to changes, recognizing limitations and incorporating team contributions.

Benefits:

• Health insurance;
• Dental insurance;
• Meal voucher;
• Food voucher;
• Transportation voucher;
• Childcare/nanny assistance;
• Complementary retirement plan;
• Life insurance.

Partnerships and perks:

• Financial products;
• Iupp;
• Pharmacy discount;
• Partner gyms, Wellhub, and Totalpass;
• Access to Itaú Unibanco clubs.

Work model and location

The position is on-site in São Paulo/SP, with a 40-hour workweek, under CLT employment.