Data Scientist, AI, ML
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Job Description
Data Scientist designing Bayesian and statistical ML models for Software Mind’s e-commerce platform client. Productionizing models within distributed microservices and event-driven architecture.
Responsibilities:
- Design and implement Bayesian statistical models for decisioning under uncertainty across pricing, segmentation, and demand-related use cases
- Build Markov chain and Hidden Markov Model formulations for sequential and behavioral patterns
- Apply MCMC methods, including Metropolis-Hastings sampling, to estimate posterior distributions and validate convergence and sampling quality
- Develop mixture models, particularly Gaussian Mixture Models, for customer or product segmentation
- Implement Expectation-Maximization for latent-variable estimation and unsupervised learning tasks
- Translate statistical models into production service architecture with APIs, data contracts, and integration points in microservices and event-driven pipelines
- Define model training, validation, versioning, monitoring, drift detection, and retraining approaches
- Partner with delivery and engineering leads to size, sequence, and estimate roadmap initiatives
- Document modeling assumptions, methodology, and validation results
- Provide handoff guidance for engineering team maintenance after the engagement
- Collaborate with backend engineering on production delivery
Requirements:
- +90% English written and oral (at least B2 level)
- Excellent communication skills
- Strong, demonstrable background in Bayesian statistics/Bayesian inference, Markov chains, Hidden Markov Models, MCMC methods including Metropolis-Hastings sampling, mixture models, ideally Gaussian Mixture Models, and Expectation-Maximization
- Proven experience building and deploying statistical/ML models into production systems
- Proficiency in Python or R with probabilistic/statistical libraries such as PyMC, Stan, scikit-learn, NumPy/SciPy
- Ability to translate statistical/mathematical models into service-oriented production architecture, defining APIs and data contracts
- Solid understanding of version control, testing practices, and CI/CD
- Strong written and verbal communication skills
- Preferred: experience in e-commerce or retail, pricing optimization, customer segmentation, or demand forecasting
- Preferred: experience integrating ML models with microservices architectures, REST/GraphQL, event-driven systems, and cloud infrastructure
- Preferred: familiarity with .NET, Java, or Node.js backend ecosystems
- Preferred: experience with MLOps tooling such as model registries, monitoring, and feature stores
- Preferred: background in pricing science, recommendation systems, or marketing analytics
Benefits:
- Flexible schedule
- Work From Anywhere
- Referral Program
- Supportive and chill atmosphere
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