Data Scientist

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PSignite

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤝 B2B

☁️ SaaS

🤖 Artificial Intelligence

B2B • SaaS • Artificial Intelligence

PSignite is a company that offers a comprehensive platform, CPGvision, for trade promotion management, optimization, and price optimization for consumer packaged goods brands. The platform integrates artificial intelligence and machine learning to enhance trade promotion and price strategy effectiveness. PSignite provides solutions for trade budget management, ROI evaluation, deduction management, and volume/spend forecasting, along with services in blueprinting, implementation, data management, and change management. The company emphasizes security, scalability, and integration with Salesforce, helping businesses maximize profitable revenue growth and optimize their operations. CPGvision is recognized for its robust, user-friendly capabilities and is trusted by leading consumer goods brands worldwide.

📋 Description

• Build and improve sales volume forecasting models using gradient boosting methods and regression techniques, including hyperparameter optimization. • Explore and prepare data for modeling, including time-series feature creation, promotion and pricing analysis, outlier detection, and data quality assurance. • Operationalize models and work within a production-grade ML pipeline leveraging cloud infrastructure. • Collaborate with business teams to interpret and communicate model outputs, translating analytical results into actionable business insights. • Test new hypotheses, evaluate alternative loss functions and algorithms, and explore improvements to existing modeling approaches. • Pursue independent research topics with the opportunity to publish findings of novel scientific value.

🎯 Requirements

• A degree in Data Science, Computer Science, Engineering, Applied Mathematics, or a related field. • Minimum 1 year of commercial experience as a Data Scientist or Machine Learning Engineer. • Proficiency in Python and core data/ML libraries (pandas, NumPy, scikit-learn, statsmodels). • Hands-on experience with gradient boosting models. • Solid understanding of time-series forecasting, regression modeling, and cross-validation techniques. • Knowledge of regression evaluation metrics in business contexts (e.g. MAE, R-squared, NRMSE). • Experience with version control systems (Git) and clean, modular coding practices (OOP). • Proficiency in SQL. • Comfortable working in a Linux environment. • Ability to present and communicate results of your work to both technical and business stakeholders, translating model outcomes into clear business value. • Communicative English, sufficient for reading documentation and presenting results.

🏖️ Benefits

• Choice of employment contract or B2B. • Fully remote work with quarterly on-site meetups (2-3 days). • Work with large, compelling analytical datasets and real impact on decisions of major corporations. • A structured research process from exploration through to production deployment. • Access to cloud computing infrastructure and a modern technology stack. • Opportunity to conduct independent research and publish results of scientific value. • Mentorship support. • Multisport card. • Private medical care.