Data Scientist – AI, ML

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Software Mind

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1999

🤖 Artificial Intelligence

☁️ SaaS

📡 Telecommunications

💰 Private Equity Round on 2020-12

Artificial Intelligence • SaaS • Telecommunications

Software Mind is a technology company that specializes in software development and digital transformation services. With a focus on AI and cloud solutions, the company offers a wide range of services including custom software development, mobile app development, and cloud consulting. Software Mind serves various industries such as financial services, telecom, biotech, and media, providing tailored solutions to accelerate digital transformations and business growth globally.

📋 Description

• 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, 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 backend engineering, defining APIs, data contracts, and microservices integration points • Define model training, validation, versioning, monitoring, drift detection, and retraining processes • Collaborate with delivery and engineering leads to size, sequence, and estimate modeling initiatives • Document modeling assumptions, methodology, and validation results • Provide handoff guidance to engineering teams for model maintainability

🎯 Requirements

• +90% English written and oral (at least B2 level) • 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, not just research notebooks or offline analysis • Proficiency in Python (or R) with standard probabilistic/statistical libraries (e.g., PyMC, Stan, scikit-learn, NumPy/SciPy) • Ability to translate statistical/mathematical models into service-oriented production architecture, defining APIs and data contracts and working directly with backend engineers • Solid understanding of version control, testing practices, and CI/CD • Strong written and verbal communication skills, with the ability to explain model behavior, assumptions, and uncertainty to non-technical stakeholders • Preferred: Experience in e-commerce or retail domains, particularly 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

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