Adidev Technologies Inc

CONVERSION LOGIX is a Digital Advertising and Technology Company based in Bothell, WA. We are hiring a Data Scientist for the Data Intelligence team! This is a remote position.

Conversion Logix is a leading marketing technology company serving the multifamily and senior-living verticals. Our platform, The Conversion Cloud®, drives lead generation, appointment scheduling, campaign attribution, and conversion optimization across hundreds of properties. We leverage cutting-edge data science and automation to deliver measurable business results.

The Opportunity:

As a Bayesian Data Scientist, you will design and deploy high-impact probabilistic models that power forecasting, attribution, pricing, experimentation, and strategic decision-making.

You will be the organization’s Bayesian subject-matter expert, developing models with PyMC and other probabilistic tools that incorporate uncertainty, allow partial pooling, enable interpretable causal effects, and operate reliably in production.

This role requires deep expertise in Bayesian inference, probabilistic programming, causal reasoning, and end-to-end data science workflow design.

What You’ll Do:

• Build and deploy Bayesian forecasting models for occupancy, demand, media performance, and conversion behavior.
• Develop hierarchical Bayesian models, state-space time-series models, Gaussian processes, and Bayesian structural time-series using PyMC at an expert level.
• Implement Bayesian attribution models and causal lift estimation integrating CRM, PMS, analytics, and advertising datasets.
• Lead Bayesian A/B testing frameworks, sequential experimentation, Bayesian optimization, and reinforcement-style decision policies.
• Conduct rigorous posterior predictive checks, sensitivity analyses, and uncertainty quantification to inform business-critical decisions.
• Build pipelines for model training, prior specification, inference (NUTS, HMC, VI), deployment, and continuous monitoring.
• Deliver uncertainty-aware insights and decision-support tooling to Product, Marketing Ops, and Client Services.
• Work with Engineering to productionize PyMC models using modern MLOps patterns, ensuring calibration monitoring and reproducibility.
• Explore advanced techniques such as Bayesian neural networks, probabilistic embeddings, and hybrid deep learning + Bayesian inference systems.

What We’re Looking For

Must-Have:

• 5+ years of experience in applied data science or statistical modeling roles, with at least 2+ years focused on Bayesian methods.
• Expert-level proficiency in PyMC — strong enough to architect complex Bayesian models, tune inference algorithms, debug sampling pathologies (e.g divergences and autocorrelation), and guide others.
• Deep experience with probabilistic programming concepts including:
• Hierarchical modeling, partial pooling, structured priors
• Bayesian regression variants: logistic/Poisson, negative binomial, zero-inflated models.
• State-space and time-series models: local level, seasonal, dynamic regression.
• Gaussian processes and non-parametric Bayesian methods
• Posterior inference with NUTS, HMC, and Variational Inference (e.g tradeoffs , convergence diagnosis)
• Strong foundation in statistical inference: likelihood theory, prior/posterior design, posterior checks, calibration assessment, causal reasoning.
• Experience with Bayesian A/B testing, treatment effect estimation, stopping rules, and causal impact modeling.
• Strong Python skills and familiarity with scientific computing libraries (NumPy, pandas, ArviZ).
• Proficiency with SQL and data engineering fundamentals (ETL, feature generation, orchestration).
• Experience deploying probabilistic models into production systems with API endpoints or batch inference.
• Ability to communicate complex statistical concepts clearly to non-technical stakeholders.
• Curiosity, rigor, ownership

Nice-to-Have:

• Familiarity with Stan, NumPyro, or TensorFlow Probability.
• Experience with marketing analytics, multi-touch attribution, media mix modeling, spend optimization or causal lift modeling.
• Background in occupancy forecasting, real-estate demand modeling, or pricing optimization.
• Experience deploying Bayesian workflows in Kubernetes/Docker environments.
• Experience with Google Cloud (BigQuery, Vertex AI).
• Exposure to Bayesian neural nets or combining deep learning with probabilistic inference.
• Exposure to simulation-based inference, approximate Bayesian computation or sequential monte carlo.

Why Join Us

• Be an early driver of agentic intelligence in a high-velocity marketing tech company.
• Shape the AI roadmap, choose tools and frameworks, own systems end to end.
• Collaborate across domains: marketing, product, engineering, data intelligence.
• Competitive salary + benefits + growth potential in a remote work model.
• Work in a culture that values innovation, experimentation, and delivering real business value.

Job Type: Full-time

Pay: $130,000.00 - $150,000.00 per year

Benefits:

• 401(k)
• 401(k) matching
• Dental insurance
• Employee assistance program
• Health insurance
• Life insurance
• Paid time off
• Vision insurance

Work Location: Remote