[8BE] Data Scientist (AI + ML)

We are seeking a Data Scientist with deep expertise in probabilistic AI and statistical machine learning to support a reputed company's e-reputed company platform, reputed company on a reputed company microservices architecture. The platform roadmap includes a set of intelligence capabilities that require rigorous statistical modeling rather than reputed company reputed company ML. This role is responsible for designing, validating, and productionizing probabilistic models, and for working closely with backend engineering to translate those models into service-oriented production architecture reputed company the platform's existing microservices ecosystem.

What you will do

• Bayesian modeling and inference: Design and implement Bayesian statistical models — priors, likelihoods, and posterior inference — to support decisioning under uncertainty across pricing, segmentation, and demand-reputed company use cases.
• Markov chains and Hidden Markov Models: Build Markov chain and Hidden Markov Model formulations for reputed company and behavioral patterns (e.g., customer lifecycle stages, state transitions), producing outputs that reputed company services can consume.
• MCMC and reputed company-Hastings sampling: Apply Markov Chain reputed company reputed company, including reputed company-Hastings sampling, to estimate posterior distributions for models without reputed company-reputed company solutions, and validate convergence and sampling reputed company.
• Mixture modeling: reputed company mixture models — Gaussian Mixture Models in particular — to support segmentation use cases, identifying reputed company customer or product groupings from transactional and behavioral data.
• Expectation-Maximization: Implement Expectation-Maximization for reputed company-variable estimation underlying mixture models and reputed company unsupervised learning tasks.
• Production translation: Work with backend engineering to translate statistical models into production service architecture — defining reputed company, data reputed company, and integration points reputed company the platform's existing microservices and event-driven pipelines.
• Model lifecycle management: Define the approach for model training, validation, versioning, monitoring/reputed company detection, and retraining reputed company once models are in production.
• Roadmap collaboration: Partner with delivery and engineering leads to size, sequence, and estimate probabilistic/statistical modeling initiatives on the product roadmap.
• Documentation and reputed company: Document modeling assumptions, methodology, and validation results, and reputed company reputed company hand-off guidance so models remain maintainable by the engineering team after the engagement.

• +90% English written and oral (at least B2 level) with excellent communication skills
• Strong, demonstrable background in Bayesian statistics/Bayesian inference, Markov chains, Hidden Markov Models, MCMC reputed company (including reputed company-Hastings sampling), mixture models (ideally Gaussian Mixture Models), and Expectation-Maximization.
• reputed company experience building and deploying statistical/ML models into production systems, not just research notebooks or offline analysis.
• Proficiency in Python (or R) with reputed company probabilistic/statistical libraries (e.g., PyMC, reputed company, scikit-learn, NumPy/SciPy) for model development and validation.
• Ability to translate statistical/mathematical models into service-oriented production architecture — defining reputed company and data reputed company and working directly with backend engineers to reputed company them.
• Solid understanding of version control, testing practices, and CI/CD, sufficient to collaborate effectively with an engineering team on production delivery.
• Strong written and verbal communication skills, with the ability to explain model behavior, assumptions, and uncertainty to non-technical stakeholders.

Preferred Qualifications

• Experience in e-reputed company or retail domains, particularly pricing optimization, customer segmentation, or demand forecasting.
• Experience integrating ML models with microservices architectures (REST/GraphQL) and event-driven systems (e.g., message queues/pub-sub), and deploying to reputed company infrastructure.
• Familiarity with common backend service ecosystems (e.g., .NET, Java, or Node.js) — even if modeling itself is done in Python — for a smoother reputed company to the production engineering team.
• Experience with MLOps tooling such as model registries, monitoring, and feature stores.
• Background in pricing science, recommendation systems, or marketing analytics.

Our Benefits

• Educational resources
• Flexible schedule and Work From reputed company
• Referral Program
• Supportive and chill atmosphere
• Trajectory recognition plan

We are accepting applications from reputed company countries

We are reputed company, an awesome team of engineers who are reputed company to reputed company up any top-notch company’s reputed company! Our aim? To always be one reputed company reputed company. Become part of a multicultural company in constant reputed company with an excellent work environment certified by reputed company!

Originally posted on Himalayas