Top Senior Data Science Jobs in Atlanta, GA

Design, build, and scale production Generative AI systems: multi-agent orchestration, advanced RAG with vector databases, LLM integration and fine-tuning, scalable FastAPI backends, Dockerized deployment, monitoring, and GenAI optimization for latency, cost, and reliability.

Design, build, and deploy production Generative AI applications: orchestrate multi-agent workflows, implement advanced RAG with vector DBs, integrate and fine-tune LLMs, develop scalable FastAPI/async backends, containerize with Docker, and optimize GenAI systems for latency, cost, and reliability.

Deliver end-to-end data science projects using machine learning and deep learning, collaborate with stakeholders, and support client engagement through analytical planning and solution design.

Own complex analyses and measurement frameworks for a product or business area. Design experiments and statistical/causal models, define and monitor KPIs, quantify impact, and translate findings into product and business recommendations. Partner cross-functionally, mentor junior analysts, and use tools like Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to scale analytics and ensure reproducibility and strong governance.

Lead research defining fabric's AI shopping roadmap: design and run quantitative studies, build models and benchmarks for AI search (AEO/GEO), run experiments, translate findings into customer-facing insights, and publish research to influence product and go-to-market strategy.

The Senior Data Scientist will design and deploy time-series forecasting models, collaborate with stakeholders, and operationalize models in cloud environments, focusing on demand planning across various industries.

Lead data science initiatives for pricing and demand forecasting using deep learning and time series methods. Design and productionalize models, communicate insights to business leaders, mentor junior data scientists, manage project priorities, and collaborate cross-functionally to drive profitable pricing decisions and scalable analytics solutions.

Develop, validate, and deploy statistical and machine learning models on large structured and unstructured tax datasets to detect fraud, prioritize audits, and score compliance risk. Clean and explore data, perform feature engineering, collaborate with stakeholders, and present technical findings to diverse audiences.

Develop, validate, and deploy predictive and statistical models on large tax and financial datasets to detect fraud and non-compliance. Perform data exploration, feature engineering, and model evaluation using Python/R, SQL, and Databricks. Collaborate with government clients and cross-functional teams, deliver technical and non-technical briefings, and ensure models are explainable, defensible, and maintainable in secure government environments.

Design and validate clinical and biomarker data pipelines, perform source-to-target mappings (e.g., EHR to data model), extend ontologies and vocabularies, ensure data quality, evaluate informatics tools, and support data architecture and analysis workflows for a regulatory-grade platform.

The Senior Data Scientist will analyze customer data, design experiments, build models, and support data-driven decision-making across product, marketing, and customer experience teams.

Lead retention and churn efforts by building survival and lifecycle-state models, classifying churn reasons, creating personalized win-back and next-best-action interventions, optimizing offers/promos, designing uplift experiments, and owning production model lifecycle, monitoring, and MLOps across Product, CRM, Marketing, and Engineering.

Lead development of Vanta's business analytics function: build scalable product data assets, define measurement frameworks, use AI-assisted analytics, partner with cross-functional teams, and deliver executive-level recommendations to drive product and business decisions.

Design, evaluate, and productionize generative AI/ML solutions (RAG, agents, embeddings, retrieval). Build evaluation frameworks for hallucination detection, benchmark LLMs, optimize prompts/models, create datasets, fine-tune models, and collaborate to deploy and monitor enterprise-scale GenAI systems.

Lead applied data science for customer experience by mining structured and unstructured data, designing experiments, building predictive models, and operationalizing solutions. Advance AI/LLM capabilities, mentor data scientists, partner with BI and data engineering to scale analytics, and communicate insights to influence business decisions.

Lead the architecture, development, and delivery of generative AI solutions. Collaborate across teams to translate requirements, monitor performance, and build scalable ML pipelines.

The Senior Data Scientist will design and implement AI solutions for supply chain problems, develop features, and collaborate with engineers and product owners.

Lead and build KLDiscovery's gen-AI architecture and core systems. Design and implement LLMs, agents, RAG, vector search, embeddings, model selection, MLOps, telemetry, and evaluation harnesses. Ship high-impact prototypes and production components, mentor senior engineers, and represent AI strategy to product, customers, and partners.

Design and evaluate predictive and generative models, extract insights from disparate clinical and product data, build and partner on data pipelines, run rigorous evaluations and experiments, and deliver time-sensitive ad hoc analyses to product, engineering, and clinical stakeholders.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

As a Senior Data Scientist, you'll optimize search relevance, retrieve content, analyze data, and collaborate with teams to enhance product strategies.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.