Please mention DailyRemote when applying
We put your well-being at the center so you can focus on technology:
π Hybrid Working & Freedom: Work from home with flexibility and comfort.
π― 30 Days Off: More time for you. You have a total of 30 days to enjoy your free time.
π Training & Tech Library: Budget, customized project training and access to resources to stay up-to-date on the latest tech stacks.
π₯ Health & Welfare: Contractual health fund extended to the family and a welfare budget tailored to your needs.
π° Referral Bonus: Do you know a talent? Introduce it to us and receive a financial reward with no referral limits.
π Plus: Electronic meal vouchers and exclusive agreements on tech, travel and lifestyle.
We are looking for professionals who are ready to make their skills available and explore new contexts or stimulating projects, or eager to deepen different areas of responsibility. If that's you, you'll be a key piece to our success thanks to:
Strong experience in forecasting models and/or promotions analytics, preferably in Retail, CPG or e-Commerce contexts
Experience in designing and maintaining demand and sales forecasting models at different levels of granularity, such as SKU, category, channel and market
Strong knowledge of classical forecasting models such as ARIMA, SARIMA, SARIMAX, ETS, Holt-Winters and state-space models
Experience with modern forecasting libraries such as Prophet, NeuralProphet, GluonTS, Statsforecast, Nixtla / MLForecast and DeepAR
Experience with XGBoost, LightGBM and CatBoost for tabular forecasting use cases
Knowledge of hierarchical forecasting and reconciliation methods such as MinT, bottom-up and top-down approaches
Proven experience in modeling price elasticity, promotional uplift and causal impact
Familiarity with approaches such as CausalImpact, Difference-in-Differences, uplift modeling and Bayesian structural time series
Strong ability to manage seasonality, intermittent demand and multi-market heterogeneity
Strong fluency with AWS, especially Amazon SageMaker and SageMaker components
Experience in implementing MLOps practices, including automated retraining, monitoring and drift detection
Solid experience with Redshift or equivalent cloud data warehouses
Production-level experience with Python, including pandas, NumPy, scikit-learn, PyTorch or TensorFlow
Ability to design and evaluate A/B tests and back-testing frameworks to validate model performance and business impact
Excellent knowledge of English (C1 level)
Nice to have:
Experience in fashion, apparel, or seasonal retail verticals.
Exposure to Power BI or similar BI tools for output consumption
The qualities we value: Collaboration is our first development tool. We are looking for professionals who aim for constant growth by valuing feedback as an opportunity for development, promote a collaboration based on transparency and co-responsibility for the success of the team and deploy their expertise with technical accuracy to ensure high-quality results.
Our selection process is streamlined, we respect your time:
HR Sync Interview: A chat to synchronize expectations, values and vision.
Technical Deep Dive: A technical peer comparison, without "school" tests, but focused on real problems and your past experiences.
Offer: If the spark is triggered, you're on board!
Send us your CV and let's start talking about your next career step!π
We believe in the value of diversity and offer equal opportunities to all qualified candidates, without distinction (L. 903/77). Your data will be treated with the utmost confidentiality for selection purposes, guaranteeing the rights provided for by the GDPR (EU Regulation 2016/679). Please do not include sensitive data in your CV unless it is strictly necessary. For more information on our privacy policy or to contact our DPO, please visit our official website.
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