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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** BINGHAMTOM UNIVERSITY - **Location:** United States - **Experience:** Expert - **Salary:** $107,000.0 - **Contract:** Permanent contract - **Skills:** Big Data, Python (Programming Language), NumPy, Salesforce.Com, Sql Optimization, Pandas, Scikit Learn, Information Technology, Statistics Packages, Machine Learning Operations, Autodesk Autocad - **Published:** September 11, 2026 - **Apply:** https://www.themuse.com/jobs/autodesk/senior-data-scientist-f2c2b2?utm_source=uconnect ## About the Role You will partner with GTM teams across Sales, Customer Success, Marketing, and Finance to quantify incremental impact, support decision-making to improve resource allocation, and elevate experimentation standards across GTM funnels. The ideal candidate combines strong statistical foundations with production-level fluency in Python and SQL and has a demonstrated ability to translate causal insights into operational decisions., * 5+ years of experience and a graduate degree in data science, computer science, applied econometrics, statistics, or related quantitative field. * Strong grounding in causal inference theory and applied methods. * Advanced proficiency in Python (e.g., pandas, NumPy, statsmodels, scikit-learn; experience with causal libraries such as DoWhy, EconML, or similar is preferred). * Advanced SQL skills with experience working on large-scale data warehouses. * Experience designing and analyzing online or field experiments. * Ability to communicate, justify and visualize complex statistical concepts for non-technical stakeholders. * Experience in B2B GTM environments (SFDC and MarTech data, sales performance, pricing, marketing mix, lifecycle optimization, or growth experimentation). * Familiarity with uplift modeling and heterogeneous treatment-effect estimation. * Exposure to Bayesian methods or hierarchical modeling. * Experience deploying models in production environments. * Experience influencing executive decision-making through formal experimentation readouts or investment cases. ## Description We are seeking a Senior Data Scientist to lead experimentation and causal inference initiatives for Autodesk's Go-to-Market Data Intelligence (GDI) organization. This role will focus on designing and deploying rigorous measurement frameworks that move beyond descriptive analytics toward defensible, decision-grade impact estimation., * Design, implement, and evaluate randomized controlled trials (A/B, geo experiments, incrementality tests). * Develop quasi-experimental frameworks (e.g., difference-in-differences, synthetic controls, regression discontinuity, instrumental variables, uplift modeling). * Define and operationalize an experimentation roadmap across GTM, including hypothesis prioritization, pre-registration standards, guardrail metrics, and clear decision thresholds for launch, scale, or sunset. * Establish best practices for experimental design, power analysis, and bias mitigation. * Design, build and productionalize causal and predictive models using Python. * Develop reusable experimentation and inference toolkits. * Conduct robustness checks, sensitivity analyses, and assumption validation. Also partner with analysts on those activities to accelerate project delivery. * Partner with data engineering to ensure high-quality, analysis-ready datasets and successful model deployment. * Transform and organize complex structured and semi-structured data sources using advanced SQL. * Construct scalable analytical datasets from large-scale transactional and behavioral systems. * Collaborate on experimentation infrastructure, including randomization frameworks and measurement pipelines. * Improve data instrumentation, logging, and tracking to enable defensible inference. * Translate statistical findings into clear, decision-oriented recommendations. * Influence GTM strategy through evidence-based resource allocation guidance. * Educate cross-functional partners on experimental design, causal reasoning, and interpretation of causal inference analytics. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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