{"id":1201515,"url":"https://alion.io/job/software-mind-8be-senior-data-scientist-probabilistic-modeling-architecture-adjacent","title":"[8BE] Senior Data Scientist, Probabilistic Modeling (Architecture, Adjacent)","company":{"id":7464,"name":"Software Mind","domain":"softwaremind.com","url":"https://alion.io/company/softwaremind","size_band":"5000+","is_staffing_agency":true,"is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Buenos Aires, Argentina"],"countries":["AR"],"hiring_countries":["AR"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":49000,"max_usd":120000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1254},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":".NET","optional":true},{"name":"C#","optional":true},{"name":"CI/CD","optional":true},{"name":"Feature Store","optional":true},{"name":"GraphQL","optional":true},{"name":"Java","optional":true},{"name":"JavaScript","optional":true},{"name":"Node JS","optional":true},{"name":"NumPy","optional":true},{"name":"Python","optional":true},{"name":"Recommender Systems","optional":true},{"name":"Rest API","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SciPy","optional":true}],"status":"live","first_seen_at":"2026-09-24T15:16:19Z","employer_posted_date":"2026-09-24","last_verified_at":"2026-09-24T21:08:10Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"We are Software Mind, an awesome team of engineers who are ready to ramp up any top-notch company’s projects! Our aim? To always be one step ahead. Become part of a multicultural company in constant growth with an excellent work environment certified by Great Place To Work!\n We're seeking a Senior Data Scientist with deep expertise in probabilistic AI and statistical machine learning to support a client's e-commerce platform. In this role, you'll design and validate probabilistic models - covering dynamic pricing, shipping cost estimation, recommendations, and segmentation - while working closely with our solution architect, the client's CTO, and the client's engineering team to shape how those models fit into the platform's architecture.\nProject Length: 3 - 6 months.\nKey Responsibilities\nBayesian modeling and inference: Design and implement Bayesian statistical models - priors, likelihoods, and posterior inference - to support decisioning under uncertainty across pricing, segmentation, and demand-related use cases.\n Markov chains and Hidden Markov Models: Build Markov chain and Hidden Markov Model formulations for sequential and behavioral patterns (e.g., customer lifecycle stages, state transitions), producing outputs that downstream services can consume.\nMCMC and Metropolis-Hastings sampling: Apply Markov Chain Monte Carlo methods, including Metropolis-Hastings sampling, to estimate posterior distributions for models without closed-form solutions, and validate convergence and sampling quality.\nMixture modeling: Develop mixture models - Gaussian Mixture Models in particular - to support segmentation use cases, identifying latent customer or product groupings from transactional and behavioral data.\nExpectation-Maximization: Implement Expectation-Maximization for latent-variable estimation underlying mixture models and related unsupervised learning tasks.\nArchitecture collaboration: Work alongside our solution architect and the client's CTO to align model design with platform architecture. While this is not an architecture-ownership role, you should be able to reason about integration points, service boundaries, and technical tradeoffs well enough to operate with a reasonable degree of autonomy and reduce the support load on the architect.\nProduction translation: Guide backend engineering on how statistical models translate into production service architecture - informing API design, data contracts, and integration points within the platform's existing microservices and event-driven pipelines.\nModel lifecycle management: Define the approach for model training, validation, versioning, monitoring/drift detection, and retraining cadence once models are in production.\nRoadmap collaboration: Partner with delivery and engineering leads to size, sequence, and estimate probabilistic/statistical modeling initiatives on the product roadmap.\n Documentation and handoff: Document modeling assumptions, methodology, and validation results, and provide clear hand-off guidance so models remain maintainable by the engineering team after the engagement.\n 90% English written and oral (at least B2 level) with excellent communication skills.\nSenior-level experience, with the ability to communicate confidently with both technical and business stakeholders, should be comfortable discussing business impact and tradeoffs directly with CTO.\nStrong, demonstrable background in designing Bayesian statistical models, Markov chains, Hidden Markov Models, MCMC methods (including Metropolis-Hastings sampling), mixture models (ideally Gaussian Mixture Models), and Expectation-Maximization - classical predictive modeling, not standard modern supervised/LLM-based ML.\nExperience designing statistical/ML models with production deployment in mind is strongly preferred; hands-on production implementation is a plus but not mandatory - the priority is the ability to architect the modeling approach and guide engineering through it.\nProficiency in Python (or R) with standard probabilistic/statistical libraries (e.g., PyMC, Stan, scikit-learn, NumPy/SciPy) for model development and validation.\nAbility to reason about how statistical/mathematical models translate into service-oriented production architecture - understanding of APIs, data contracts, and how to work directly with backend engineers and architects to integrate models.\nSolid understanding of version control, testing practices, and CI/CD, sufficient to collaborate effectively with an engineering team on production delivery.\nStrong written and verbal communication skills, with the ability to explain model behavior, assumptions, and uncertainty to non-technical stakeholders.\n Preferred Qualifications/Nice to have\nExperience in e-commerce or retail domains, particularly pricing optimization, customer segmentation, or demand forecasting.\nFamiliarity with how ML models integrate into microservices architectures (REST/GraphQL) and event-driven systems (e.g., message queues/pub-sub) hands-on deployment experience is a plus but not expected.\nFamiliarity with common backend service ecosystems (e.g., .NET, Java, or Node.js) even if modeling itself is done in Python - for a smoother handoff to the production engineering team.\nExposure to MLOps concepts such as model registries, monitoring, or feature stores - helpful for handoff conversations, but not a core requirement.\nBackground in pricing science, recommendation systems, or marketing analytics.\nExperience communicating modeling recommendations directly to business or executive stakeholders (e.g., CEO/CTO-level conversations).\nWe are accepting applications from LATAM countries","description_format":"text","description_chars":5639,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"Argentina","iso":"AR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Commerce"],"lifecycle":[{"event":"open","at":"2026-09-24T21:08:10Z"}],"liveness":{"score":52,"band":"ok","label":"Likely open","p_open":1,"p_active":0.516,"p_room":1,"age_days":0,"expected_fill_days":18,"reasons":["conf:2","agency","win:early"],"computed_at":"2026-09-24T23:41:15Z"},"pay":null,"html_url":"https://alion.io/job/software-mind-8be-senior-data-scientist-probabilistic-modeling-architecture-adjacent","json_url":"https://alion.io/job/software-mind-8be-senior-data-scientist-probabilistic-modeling-architecture-adjacent.json","meta":{"generated_at":"2026-09-24T23:41:15Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1876,"day_limit":5000,"remaining_today":3124,"minute_limit":60,"resets_at":"2026-09-25T00:00:00Z"}}}