Senior Data Scientist, Statistical Modeling

This is a fully remote position, open to applicants in Romania, +1 more country.

📋 Description

• Create and validate probabilistic models for an e-commerce platform.

• Develop models for dynamic pricing, estimating shipping costs, providing recommendations, and segmenting customers/products.

• Design and implement Bayesian statistical models, incorporating priors, likelihoods, and posterior inference.

• Construct Markov chain and Hidden Markov Model formulations to analyze sequential and behavioral patterns.

• Utilize MCMC methods, including Metropolis-Hastings sampling, to validate convergence and assess sampling quality.

• Develop mixture models, especially Gaussian Mixture Models, for effective segmentation.

• Implement Expectation-Maximization for latent-variable estimation and unsupervised learning techniques.

• Collaborate with the solution architect and the client's CTO to ensure alignment on platform architecture.

• Provide guidance to backend engineering on production translation, API design, data contracts, and microservice/event-driven integration.

• Establish approaches for model training, validation, versioning, monitoring, drift detection, and retraining.

• Partner with delivery and engineering leads to size, sequence, and estimate modeling initiatives.

• Document modeling assumptions, methodologies, validation results, and provide handoff guidance.

⛳️ Requirements

• Proficiency in English, both written and spoken, at a minimum B2 level (90% proficiency).

• Senior-level experience confidently communicating with both technical and business stakeholders, including discussions at the CTO level.

• Proven expertise in designing Bayesian statistical models, Markov chains, Hidden Markov Models, MCMC methods such as Metropolis-Hastings, mixture models including Gaussian Mixture Models, and Expectation-Maximization.

• Background in classical predictive modeling rather than standard modern supervised/LLM-based machine learning.

• Preferred experience in designing statistical/ML models with an emphasis on production deployment; hands-on production implementation is an advantage but not required.

• Proficiency in Python or R.

• Experience with probabilistic/statistical libraries like PyMC, Stan, scikit-learn, and NumPy/SciPy.

• Ability to translate statistical/mathematical models into a service-oriented production architecture.

• Understanding of APIs, data contracts, backend engineering collaboration, and architecture integration.

• Strong grasp of version control, testing practices, and CI/CD methodologies.

• Excellent written and verbal communication skills.

• Preferred experience in the e-commerce or retail sectors.

• Familiarity with REST/GraphQL, microservices, and event-driven systems is preferred.

• Familiarity with .NET, Java, or Node.js backend ecosystems is preferred.

• Exposure to MLOps concepts such as model registries, monitoring, or feature stores is preferred.

• Background in pricing science, recommendation systems, or marketing analytics is preferred.

• Experience in communicating modeling recommendations to business or executive stakeholders is preferred.

🏝️ Benefits

• Outstanding work environment recognized by Great Place To Work.

• Option for remote work.

• Project engagement lasting between 3 to 6 months.