Statistician / Quantitative Modeler

Statistician / Quantitative Modeler AI Systems • Multi-Modal Predictive Modeling • Research Analytics Contract (3–12 months) | Remote (EST or CST time zones preferred) | Contract or Contract-to-Hire. We are open to candidates that can work full-time 40 hours/wk or even candidates that can work part-time – off hours as a 2nd job – nights/weekends/free-time. Our key focus is on finding the right person. Expert Technical Solutions has an immediate opening for a Statistician / Quantitative Modeler. Our client is developing an immersive AI experience that merges storytelling, interactivity, and advanced design to shape how people engage with new ideas. The project sits at the intersection of creativity and technology, aiming to deliver something truly next generation in look, feel, and purpose. They are currently in stealth mode and expanding their team with an AR/VR developer who can help craft a cinematic, real-time experience that pushes visual and interactive boundaries. We are seeking a highly skilled Statistician / Quantitative Modeler to join our team advancing the next generation of AI, avatar, and multi-modal systems. This role involves developing rigorous quantitative frameworks, validating predictive models, and performing high-level data analysis to ensure the reliability and performance of complex AI and ML systems. You will collaborate directly with our CTO and research engineers to bring scientific precision and statistical integrity to production-level AI applications. Key Responsibilities Design and implement statistical frameworks for evaluating multi-modal AI models (vision, voice, text). Develop and validate predictive modeling pipelines supporting AI/ML research and product development. Lead experimental design and A/B testing for avatar systems, speech synthesis, and real-time inference performance. Conduct advanced statistical analyses using Bayesian methods, mixed models, GLMs, and survival models. Build and maintain validation datasets, benchmarking tools, and testing scripts for ML and graphics algorithms. Analyze performance metrics such as voice synthesis quality, lip-sync accuracy, and audio-emotion mapping. Support research reporting through quantitative analysis, visualizations, and reproducible documentation. Partner with engineering teams to embed statistical rigor directly into production pipelines. Core Technical Skills Statistical & Analytical Expertise Hypothesis testing, inferential statistics, regression (linear, logistic, Poisson). Bayesian inference, mixed-effects modeling, and generalized linear models. Time-series and signal analysis, power analysis, and experiment design. Strong understanding of multimodal data evaluation (audio, visual, and text). Tools & Programming Proficiency in R • or Python • (NumPy, SciPy, Statsmodels, PyMC, scikit-learn). Experience with R Markdown, Jupyter, or Shiny dashboards. SQL for structured data queries and analysis. Familiarity with ML evaluation metrics and data preprocessing. Experience maintaining reproducible research workflows. Data & Model Validation Evaluate ML model performance using statistically sound methods. Develop custom validation metrics for TTS systems, voice similarity, and viseme alignment. Construct benchmark datasets and validation pipelines for AI/ML deliverables. Conduct statistical quality control (QC) for data inputs, model outputs, and experiment logs. Qualifications Required: 5+ years of applied statistics or quantitative modeling experience. Proven expertise in experimental design and statistical modeling. Demonstrated success supporting ML or research teams with quantitative insights. Experience working with multidimensional or multimodal datasets. Portfolio of published analytical work, dashboards, or research outputs. Preferred: Experience validating AI, voice synthesis, or computer vision systems. Background in computational or applied research. Experience with signal processing or real-time inference systems. Publications in applied statistics, AI, computational modeling, or biomedical informatics. Familiarity with GPU-based ML workflows and lifecycle management. Core Principles Scientific Rigor: Decisions driven by validated statistical evidence. Model-First Thinking: Deep understanding of data integrity and its impact on AI performance. Reproducibility: All results must be transparent, explainable, and repeatable. Clarity: Ability to communicate insights to both technical and non-technical teams. Collaboration: Work seamlessly with AI/ML, engineering, and product teams to translate data into impact. Job Type: Contract Pay: $50.00 - $70.00 per hour Benefits: Dental insurance Health insurance Vision insurance Work Location: Remote