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3 results for Cloud Computing Analyst in Atlanta, GA

Cloud Engineer

Atlanta, GA
onsite
Temporary / Contract
60 - 65 USD / Hourly
We are seeking an Azure Cloud Engineer to design, implement, and support scalable, secure, and highly available Azure cloud environments. This role will be responsible for cloud infrastructure deployments, migrations, automation, monitoring, and optimization while partnering with infrastructure and security teams to implement cloud best practices.
2026-07-14T00:00:00Z

Data Scientist

Atlanta, GA
onsite
Permanent / Full Time
120000 - 140000 USD / Yearly
We are looking for a Data Scientist to join a fast-moving IT consulting environment in Atlanta, Georgia. This role focuses on turning complex data into practical business insights, with a strong emphasis on forecasting, predictive modeling, and customer-focused problem solving. The ideal candidate combines advanced machine learning expertise with hands-on data preparation skills and can clearly explain how analytical work influences end users and business outcomes. Responsibilities: • Build, validate, and refine forecasting and predictive models using Python and modern machine learning frameworks for business-driven use cases. • Develop analytical solutions with tools such as scikit-learn, XGBoost, LightGBM, and time-series or deep learning methods based on project needs. • Use Databricks and Apache Spark to process large datasets efficiently and support scalable model development workflows. • Prepare, transform, and organize data by writing queries, performing ETL tasks, and improving data quality for downstream analysis. • Translate technical findings into clear recommendations for clients and stakeholders, emphasizing business impact and user experience. • Partner with customer-facing teams to define problem statements, shape data-driven approaches, and deliver actionable insights in a fast-paced setting. • Apply product thinking when designing models and analytical outputs to ensure solutions align with customer needs and practical use. • Contribute domain knowledge to projects involving retail or consumer goods data, helping tailor models to industry-specific patterns and challenges.
2026-07-17T00:00:00Z

Senior Data Scientist

Atlanta, GA
onsite
Permanent / Full Time
160000 - 180000 USD / Yearly
Our client is seeking a Senior Data Scientist to join their Data & Analytics organization and lead the development of advanced machine learning and predictive analytics solutions. This role is ideal for a hands-on data science leader who enjoys solving complex business problems, building production-level ML models, and partnering with cross-functional teams to deliver measurable business impact. The Senior Data Scientist will play a key role in developing and operationalizing machine learning solutions across areas including risk, fraud, customer analytics, marketing, and portfolio management. The successful candidate will bring strong technical expertise across the full machine learning lifecycle and the ability to translate complex data insights into actionable business recommendations. Responsibilities Lead the design, development, validation, deployment, and monitoring of machine learning and predictive analytics solutions. Build, optimize, and maintain production-grade models that drive business outcomes across risk, fraud detection, customer behavior, marketing analytics, and portfolio management. Perform exploratory data analysis, feature engineering, statistical analysis, and hypothesis testing to identify trends and actionable insights. Develop scalable analytics solutions using large structured and unstructured datasets. Translate complex analytical findings into clear recommendations for technical teams, business stakeholders, and leadership. Create dashboards, visualizations, and reporting solutions to communicate model performance, insights, and business impact. Partner with data engineering teams to define data requirements, improve data pipelines, and ensure data quality. Establish and promote best practices around machine learning development, MLOps, model governance, and analytics processes. Lead proof-of-concept initiatives evaluating emerging machine learning techniques and AI technologies. Own the complete model lifecycle, including feature engineering, training, validation, deployment, monitoring, retraining, and optimization. Mentor entry level data scientists through technical guidance, code reviews, and knowledge sharing. Provide technical leadership around modeling strategies, architecture decisions, and analytical methodologies.
2026-07-24T00:00:00Z