Top Data Science Jobs in Huntsville, AL

Design, develop, and deploy NLP and LLM-powered models to extract intent, outcomes, and sentiment from calls, chats, and digital interactions. Translate unstructured interactions into actionable insights, build evaluation frameworks, debug and improve model performance, and hand off production-ready artifacts to data engineering to improve call center efficiency and customer experience.

Lead data-driven strategy by partnering with senior executives, design and deliver sophisticated analytical solutions on large-scale data, build trusted cross-functional relationships, and mentor data scientists to raise analytical quality across the organization.

Lead data-driven strategy by partnering with senior executives to deliver rigorous analytical solutions. Design and implement sophisticated analyses on large-scale data, build trusted cross-functional relationships, mentor data scientists, and influence long-term product and business decisions.

The Staff Data Scientist will design and optimize deep learning models for fraud detection, mentor peers, and lead data science initiatives.

Design, validate, and deploy scalable statistical and distributional models for enterprise consumer analytics. Implement rigorous methodologies, convert ad-hoc analyses into version-controlled analytical libraries, and partner with Data Engineering to optimize performance and scale compute workloads (including cloud/Databricks). Deliver reproducible analytics powering dashboards and LLM-driven applications, with a focus on panel and transaction-level consumer data.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.

Design and fine-tune LLMs and RAG pipelines to parse regulatory texts and extract executable rules; build forecasting, classification, and risk-scoring models for supply chain; design robust data extraction and transformation pipelines (ERP/SAP, Data Lakehouse); integrate models via APIs; optimize performance and validate outputs to achieve production-grade reliability.

Lead a 5–8 person Data Science team to develop and operationalize FWA detection models using SAS and Python on multi‑payer healthcare claims. Oversee model development, data pipelines, quality reviews, stakeholder presentations, and collaboration with SMEs and BI developers. Split role ~40% management, 60% hands-on coding/analysis.

Design, build, and deploy predictive GTM models (LTV, attribution, propensity). Lead experimentation and causal analyses, define KPI measurement frameworks, partner with Data Engineering, and translate statistical insights into actionable recommendations for Sales, Marketing, and Customer Success.

Lead development of meteorological and weather-driven analytics for commercial operations: collect and analyze atmospheric datasets, build predictive/prescriptive models using NWP outputs, translate results for stakeholders, coordinate cross-functional teams, mentor analysts, and ensure maintainable decision-support tools aligned with business objectives.

Develop and tune ML models, productionize and deploy strategies for ML systems, and align cross-functionally to communicate performance metrics.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Lead end-to-end machine learning and advanced analytics projects: frame problems, build and deploy predictive/prescriptive models, design ETL pipelines, create dashboards and A/B test metrics, and deliver actionable insights to business stakeholders to improve fleet, pricing, and ridesharing products.

Lead the data science strategy for deployed humanoid robots: build predictive maintenance and reliability models, drive fleet performance and RaaS economics analysis, develop anomaly detection and RCA tooling, link manufacturing test data to field outcomes, and set instrumentation, experimentation, and data-quality standards across hardware, software, manufacturing, and operations.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.

The Senior Data Scientist oversees data collection and preparation, designs study protocols, leads report development, trains junior employees, and manages project workstreams while collaborating with team members to optimize business performance.

The Senior Data Scientist will integrate data from various sources, analyze web performance, and provide insights for strategic decision-making. Responsibilities include developing automated systems for content coverage, tracking metrics, and designing experiments to assess new initiatives' impact.

Lead customer-facing data science engagements: acquire and prepare data, evaluate and operationalize models at scale, drive modeling best practices, research industry trends, write extensible code, and define solution and customer strategy while promoting ethics and privacy.

Build, deploy, and iterate production ML models for marketplace problems (ranking, personalization, renter intent, demand/supply optimization). Own end-to-end projects including feature engineering, modeling, A/B testing, monitoring, and cross-functional communication with Product, Engineering, and Analytics.

Lead org-wide business intelligence and experimentation efforts: build dashboards and metrics, design and analyze A/B and multivariate experiments, develop predictive and behavioral models, and translate insights into decision-ready recommendations across product and business functions.

As a Data Scientist III, you'll build customer identity systems, develop recommendation models, predictive analytics for customer behavior, and collaborate with ML Ops and Data Engineering.

Lead end-to-end delivery of strategic data science and AI projects: define business problems with stakeholders, prepare large datasets, build and deploy predictive, prescriptive, and generative AI models (including LLMs), implement prompt engineering and fine-tuning, ensure production-grade code and ML lifecycle practices, present insights to senior stakeholders, and promote responsible AI and adoption across teams.

The Senior Data Scientist will lead innovative data science efforts, leveraging advanced analytics, visualization, and insights from complex datasets to boost productivity.

Lead embedded data science for a core business area (growth, product, AI, or partnerships). Define problems, build metrics and analyses, run experiments, surface insights, and drive actionable recommendations end-to-end to improve key business metrics.

Embed on a business unit to define problems, build metrics/reports/experiments, analyze data, and drive decisions end-to-end across growth, product, AI, or partnerships.