Senior Data Scientist

AVANTTi

. Develop and calibrate hierarchical demand forecasting models, considering seasonality, regression levels, and features related to calendar, availability, and pricing .

Posted 9/22/2026full-timeRemote • BrazilSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and calibrating hierarchical demand forecasting models, applying rigorous statistical validation, and collaborating with cross-functional teams to support strategic business decisions. Proficient in advanced Python and PySpark, with a strong foundation in statistical methods and experience in MLOps tools.

Highest-signal resume keywords

Hierarchical Demand ForecastingAdvanced Python SkillsTime Series AnalysisStatistical ValidationMLOps Tools

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Time Series AnalysisForecastingStatistical ModelingRegression ModelsExperimental DesignHoldout TestingTemporal ValidationCounterfactual AnalysisHierarchical Forecast ReconciliationData Pipeline Management

Soft Skills

Clear CommunicationMentorship

Tools & Technologies

PySparkAWS GlueAWS S3AWS Step FunctionsMLflowTerraform

Industry Keywords

Fashion SectorRetail SectorMerchandising Hierarchies

Tech Stack

Tools & technologies

AWSPySparkPythonTerraform

About the role

Key responsibilities & impact

Develop and calibrate hierarchical demand forecasting models, considering seasonality, regression levels, and features related to calendar, availability, and pricing
Design and conduct backtests and counterfactual analyses to compare decision policies
Apply rigorous statistical validation before implementing changes in production
Work with data pipelines at scale, ensuring experiment reproducibility, quality, and traceability
Partner with Engineering and MLOps teams on model deployment and management, including MLflow
Collaborate with business functions, such as Procurement, Pack, and Assortment, ensuring forecasts support strategic decisions
Document decisions, experiments, learnings, and results in a structured manner
Lead end-to-end technical investigations, from problem analysis through recommendation
Provide technical support and mentorship to more junior professionals

Requirements

What you’ll need

Bachelor’s degree in Statistics, Economics, Engineering, Mathematics, Systems Analysis, or a related field
Solid experience with time series and forecasting
Advanced Python skills
Experience with PySpark in distributed environments, such as AWS Glue, EMR, or similar platforms
Strong statistical foundation in regression models, seasonality, hierarchical forecast reconciliation, experimental design, holdout testing, temporal validation, and counterfactual analysis
Experience with AWS, especially S3, Glue, and Step Functions
Methodological rigor in designing experiments, isolating variables, and determining whether a result is conclusive
Clear communication skills to translate technical results into business decisions
Preferred: experience with MLflow, experiment tracking, and model registry tools, or equivalent MLOps tools
Preferred: experience with Terraform / Infrastructure as Code (IaC)
Preferred: experience in the fashion and/or retail sector
Preferred: experience working with complex merchandising hierarchies

Benefits

Comp & perks

CLT employment contract
100% remote work — permanent remote arrangement
Project duration of 5 to 11 months, with the possibility of extension