Data Scientist

• Develop statistical and machine learning solutions for manufacturing, test, quality, and production challenges
• Explore large and complex datasets to identify patterns, process drivers, anomalies, and improvement opportunities
• Build and deploy Python-based analytical and machine learning applications for engineers and factory teams
• Partner with engineers, operators, and technical stakeholders to translate problems into practical data solutions
• Develop visualizations and analytical tools that make complex data actionable
• Establish sustainable approaches for deploying, monitoring, and maintaining machine learning solutions
• Mentor data scientists and engineers and contribute to technical direction and best practices
• Build expertise in factory and test data to identify opportunities for data science and automation
• Transition successful solutions from prototypes into production to influence engineering and manufacturing decisions

Senior Data Scientist – Factory Intelligence

• Manage teams responsible for ingesting, processing, and/or delivering files across the enterprise
• Set clear standards and measurements for team performance
• Coordinate with Team Leads and Individual Contributors to understand performance trends and solve business challenges
• Collaborate with cross-functional teams on business requirements for client implementations, issue resolution, renewals, and change requests
• Collaborate on requirements for new or enhanced product features
• Provide direction and support for leadership development
• Own sections of the data pipeline, including handoffs, monitoring, quality controls, and workflow management
• Oversee comprehensive documentation of data analysis and data engineering processes, architecture, and workflows
• Design, build, and maintain data pipelines, data models, and data solutions
• Analyze mappings of insurance claims, import/export files, and eligibility files for troubleshooting
• Identify technical issues from improper enrollment or enrollment changes on EDI files and coordinate resolution with engineering partners
• Coordinate client implementation and EDI testing, implementations, and upgrades
• Translate business requirements into actionable solutions aligned with organizational goals
• Create ad hoc SQL queries to support Operations
• Build and maintain file transmissions through file transfer tools such as GoAnywhere and MoveIt

Manager, Data Operations Integrations

• Lead the transformation of data from a reporting and analytics function into a strategic product capability
• Define and drive the company’s data vision, strategy, and roadmap
• Build, lead, and develop the data organization across data engineering, analytics, and data science
• Manage and develop a high-performing team of nine
• Partner with cross-functional leaders to translate company objectives into scalable data solutions, platforms, and insights
• Shape the technical direction of the data platform with the Staff Data Engineer
• Contribute to architecture, design, and implementation of critical systems and solutions
• Establish engineering standards, best practices, and design patterns across the data ecosystem
• Drive data modeling, quality, governance, security, observability, and validation practices
• Lead the design, implementation, and operation of AWS cloud-based data infrastructure and services
• Prioritize investments in data platforms, tooling, and processes
• Influence company-wide technology strategy as a member of the engineering leadership team

Head of Data

• Guide Wikipedia’s anti-abuse and security strategy as a member of the Product Analytics team
• Collaborate with product managers, engineers, designers, research scientists, security engineers, and other colleagues
• Inform product development strategy and evaluate the impact of features and interventions
• Set measurement strategy for detecting bots and inauthentic account activity
• Analyze and develop heuristics and approaches to detect potentially abusive activity
• Help develop and evaluate AI models to identify malicious user-authored code
• Make recommendations on product direction and data strategy
• Deliver quantitative data and insights to inform strategy and product decisions
• Communicate results and data-backed recommendations to cross-functional stakeholders
• Build and execute measurement strategies and evaluate experiments using Bayesian and Frequentist approaches
• Perform quantitative research
• Develop queries and code for large-scale internal and external data repositories using Apache Iceberg, Hive, Druid, Presto, and Spark
• Build automated self-service dashboards using DBT, Airflow, and Superset
• Help teams instrument features, perform data quality assurance, and use A/B testing tools
• Prioritize workload and select appropriate analytical methods

Senior Data Scientist, Safety & Security

• Perform MIS-related duties assigned by the department under general supervision
• Assist with deployment of ensemble machine learning methods, deep learning, and advanced optimization techniques
• Test hypotheses and draw insights from large mining datasets
• Support the building, implementation, and maintenance of practical analytical assets using statistical methodologies
• Use modern cloud technologies such as Microsoft Azure to deliver analytics solutions at scale
• Visualize analytics impact for leadership
• Work scheduled and unscheduled overtime or outside normal working hours when required

Summer Internship – MIS Data Science

• Gather, interpret, and manipulate structured and unstructured data for advanced analytical solutions
• Develop scalable, automated solutions using machine learning, simulation, and optimization
• Select modeling techniques and technologies based on data limitations, application, and business needs
• Develop and deploy models within the Model Development Control and Model Risk Management frameworks
• Compose technical documents for knowledge persistence, risk management, and technical review audiences
• Assess business needs and recommend analytical and modeling projects
• Prioritize analytics and modeling problems and research efforts with business and analytics leaders
• Contribute to reusable, production-quality algorithms and supporting code
• Translate business requests into analytical questions, execute analyses and modeling, and communicate outcomes with business recommendations
• Collaborate with Data Engineering, IT, business teams, and internal stakeholders to deploy production-ready analytical assets
• Maintain awareness of cutting-edge techniques
• Pursue opportunities to learn new techniques, technologies, and methodologies
• Identify, measure, monitor, and control risks in accordance with risk and compliance policies and procedures

Data Scientist jobs in Arizona

Senior Data Scientist – Factory Intelligence

Manager, Data Operations Integrations

Head of Data

Senior Data Scientist, Safety & Security

Summer Internship – MIS Data Science

Data Scientist – Risk Modeling