Senior Data Scientist, Statistical Modeling

Job not on LinkedIn

🔥 12 hours ago

🌐 Romania, Argentina – Remote

🇷🇴 Romania – Remote 🇦🇷 Argentina – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 15%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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 validate probabilistic models for an e-commerce platform • Develop models for dynamic pricing, shipping cost estimation, recommendations, and customer/product segmentation • Design and implement Bayesian statistical models, including priors, likelihoods, and posterior inference • 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 segmentation • Implement Expectation-Maximization for latent-variable estimation and unsupervised learning • Collaborate with the solution architect and client's CTO on platform architecture alignment • Guide backend engineering on production translation, API design, data contracts, and microservice/event-driven integration • Define model training, validation, versioning, monitoring, drift detection, and retraining approaches • Partner with delivery and engineering leads to size, sequence, and estimate modeling initiatives • Document modeling assumptions, methodology, validation results, and handoff guidance

🎯 Requirements

• 90% English written and oral proficiency, at least B2 level • Senior-level experience communicating confidently with technical and business stakeholders, including CTO-level discussions • Demonstrable expertise designing Bayesian statistical models, Markov chains, Hidden Markov Models, MCMC methods including Metropolis-Hastings, mixture models including Gaussian Mixture Models, and Expectation-Maximization • Experience with classical predictive modeling rather than standard modern supervised/LLM-based ML • Experience designing statistical/ML models with production deployment in mind preferred; hands-on production implementation is a plus but not mandatory • Proficiency in Python or R • Experience with probabilistic/statistical libraries such as PyMC, Stan, scikit-learn, NumPy/SciPy • Ability to translate statistical/mathematical models into service-oriented production architecture • Understanding of APIs, data contracts, backend engineering collaboration, and architecture integration • Solid understanding of version control, testing practices, and CI/CD • Strong written and verbal communication skills • Experience in e-commerce or retail domains preferred • Familiarity with REST/GraphQL, microservices, and event-driven systems preferred • Familiarity with .NET, Java, or Node.js backend ecosystems preferred • Exposure to MLOps concepts such as model registries, monitoring, or feature stores preferred • Background in pricing science, recommendation systems, or marketing analytics preferred • Experience communicating modeling recommendations to business or executive stakeholders preferred

🏖️ Benefits

• Excellent work environment certified by Great Place To Work • Remote work option • Project engagement of 3–6 months