Top Data & Analytics Jobs

The Forecasting Manager is responsible for demand forecasting accuracy, managing forecasts using machine learning, and training marketing & sales teams. Collaborates with top management to ensure forecast consistency and leads process optimization projects.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate and operationalize ML models, optimize Hadoop/HDFS workflows, ensure data quality, and collaborate with data science to support analytics and reporting needs.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts. Integrate data from multiple sources, ensure data quality, optimize Hadoop/HDFS workflows, collaborate with Data Science to operationalize models, and recommend tooling and system improvements.

Build and maintain large-scale data structures, pipelines, and ETL workflows; design databases and data marts; collaborate with Data Science to integrate models; ensure data quality and accessibility; leverage Hadoop, Spark, Python/Java, and cloud platforms to deploy scalable ML-enabled data solutions.

Design and deliver predictive analytics and ML solutions to improve customer engagement and experience. Perform ad-hoc analyses (SQL, Tableau, Excel), build statistical and NLP models, partner with stakeholders and engineering to deploy data solutions, and evaluate/optimize multi-channel campaigns.

Lead development and implementation of data science and analytics solutions: apply data mining, statistical and predictive modeling, ML, ETL, and BI/dashboarding to large healthcare datasets; communicate insights to stakeholders; design experiments; mentor junior staff; set analytics strategy and priorities.

Design, build, and maintain large-scale data structures, ETL pipelines, and data marts to support analytics and Data Science. Collaborate with Data Science to integrate models, ensure data quality and accessibility, optimize cloud queries (GCP/AWS), troubleshoot systems, and recommend tooling and solutions to meet business requirements.

Design and develop scalable data solutions and ETL pipelines ingesting healthcare and retail data; build predictive models and statistical analyses; support deployment of insights across channels; collaborate on backend services, DevOps, and cloud cluster management to solve complex business problems.

Design and deliver data-driven analytic solutions and models for healthcare initiatives. Perform large-scale data analysis, predictive modeling, ETL and data warehousing, create reports/visualizations, and present findings to stakeholders to inform program design and evaluation.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.

The role involves designing and implementing advanced analytics solutions for healthcare payers, analyzing complex problems, mentoring juniors, and building client relationships.

Evaluate and create AI-generated content in German. Review writing for factuality, completeness, and grammar while producing original content.

Lead development of advanced analytical and machine learning models to optimize forecasting, inventory placement, and supply chain flows. Automate reports, analyze large datasets, deliver insights to leaders, drive cross-functional initiatives, mentor junior analysts, and recommend process improvements to boost operational performance.

Design, build, and maintain forecasting and analytical models, ETL/ELT pipelines, dashboards, and production-grade model deployments. Analyze operational and financial data, develop KPIs, support executive strategic inquiries, and partner cross-functionally to translate data into actionable insights while embedding AI to scale workflows.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

Maintain and improve analytics solutions and financial/marketing models (primarily in Excel); perform ETL/data wrangling; analyze market and business data; communicate concise insights to stakeholders; drive data-informed strategic decisions and build production-ready data products or pipelines.

The Senior Manager of Data Insights will lead a team to optimize data sharing and governance, develop data strategies, and deliver actionable business intelligence across Docker's operations.

The Senior Product Manager will lead strategy and execution for data products within the Global Data & Analytics team, focusing on analytics, ML, and AI use cases while partnering with engineering and stakeholders to deliver scalable solutions.

The Quantitative Analyst will develop stock selection models, enhance research infrastructure, conduct statistical analysis, and collaborate with investment teams to provide insights.

Design and implement Tableau BI solutions; work with Big Data stack (Hive, Pig, MapR, Spark); develop ETL (Datastage, Unix scripting); apply Scala/Python for machine learning; leverage AMEX domain expertise.

Design and deliver full lifecycle enterprise and big-data architectures, translate complex functional and technical requirements into detailed designs, lead presales and client presentations, perform advanced analytics and ML modeling (logistic/linear regression, random forest, neural networks, time series), define data requirements and analytical plans, and collaborate with cross-functional teams and stakeholders.

Design and architect data solutions and large-scale Java/J2EE systems. Define extensibility, scalability, availability and security requirements. Document current and target state, gather functional and non-functional requirements, recommend process optimizations, and consider impacts of existing infrastructure and networks.

Design, build, and maintain scalable ETL/ELT pipelines and batch/streaming data platforms. Develop APIs, manage databases, containerize applications (Docker/Kubernetes), implement CI/CD, and lead cross-functional teams to deliver mission-focused analytics solutions. Requires travel and TS/SCI clearance.

Develop and optimize high-volume Teradata data warehouse applications: design/architect solutions, model data, write and tune SQL, use Python scripting; ML and Hadoop experience a plus.

Lead design and build of a cloud-based big data analytics platform: implement analytics infrastructure, integrate streaming and batch data, develop distributed processing pipelines, manage predictive analytics models, and apply machine learning and Bayesian methods. Work involves Scala on OS X and AWS, Java and Clojure, Kafka/Samza, NoSQL, and following TDD, Agile, CI/CD practices.