Data Scientist, Mid-level

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Mercafacil

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2015

🛍️ eCommerce

🤝 B2B

🛒 Retail

💰 Venture Round on 2021-12

eCommerce • B2B • Retail

Mercafacil is a technology company designed to enhance the retail sector, particularly supermarkets, by utilizing customer behavior data to optimize sales strategies. Their comprehensive solutions integrate CRM, e-commerce, and trade promotions to improve customer retention and increase average transaction values. With over 4,500 stores using their platform and 100 integrated ERPs, Mercafacil aims to streamline operations and drive profitability for their clients in both physical and online retail environments.

📋 Description

• You will bring statistical rigor to business decisions. • Within the BI team, your mission is to go beyond descriptive analysis by applying statistical and machine learning models to find patterns, validate hypotheses, and generate forecasts that guide real strategies. • Day-to-day, you will model complex problems with Python, work with large volumes of data in ClickHouse and BigQuery, and collaborate with product and operations teams to ensure the models deliver real value. • Conduct statistical analyses to answer business questions: hypothesis testing, correlation analysis, segmentation, and predictive modeling; • Perform exploratory data analysis (EDA) to understand the data before modeling, identifying patterns and inconsistencies; • Write complex SQL queries in ClickHouse and BigQuery to extract and prepare data for analysis and modeling; • Use Python for data manipulation, exploratory analyses, and model prototyping; • Communicate results and insights clearly to business teams—translating statistics into decisions; • Collaborate with the BI team to define metrics, data quality standards, and analytical best practices; • Monitor models in production, tracking performance and proposing continuous improvements;

🎯 Requirements

• Enrolled in a bachelor’s degree in Statistics, Computer Science, Engineering, Mathematics, or a related field; • Proficiency in Python for data analysis; • Strong applied statistics knowledge: hypothesis testing, regression, distributions, confidence intervals; • Experience with supervised modeling: classification, regression, and familiarity with model evaluation metrics (MAPE, RMSE, etc.); • Solid SQL skills for complex analyses (CTEs, window functions, large-scale aggregations); • Development best practices: organized code, use of Git, basic testing; • Ability to work autonomously and communicate effectively with stakeholders from different areas; • Experience with ClickHouse and BigQuery; • Retail domain knowledge; • Experience with Spark for large-scale data processing and analysis; • Familiarity with orchestration or model versioning tools (Airflow or similar); • Portfolio with analyses or projects that demonstrate applied statistical reasoning.

🏖️ Benefits

• Medical insurance through SulAmérica or Central Nacional Unimed depending on predominant region for you and your dependents with no monthly fee, subject to copay based on usage; • Dental insurance through Odontoprev for you and your dependents with no monthly fee, subject to copay based on usage; • Dasa telemedicine offering various online consultations without the need for referrals and no copay; • "Meu Doutor" family doctor service available to enrolled employees and dependents on the medical plan; • Pregnancy program (for employee or dependent), supporting a safer and more comfortable experience during pregnancy, delivery, and postpartum; • Free influenza vaccination for you and your dependents; • Prevenar 13 vaccine to help protect against 13 types and subtypes of pneumococcal bacteria; • Life insurance; • Wellhub; • Extended maternity and paternity leave; • Flexible benefits via Caju card (meal and food allowances - VR/VA); • Birthday-off so you can celebrate your birthday; • Day-off for moving house; • Extended honeymoon leave to enjoy your honeymoon calmly; • No dress code; • Performance reviews; • Corporate University (training); • Culture of feedback and frequent 1:1s.