To work in collaboration with business and O&M on creating value from data, solving complex problems by turning vast amounts of data into business insights through advanced analytics, modeling, and machine learning.
Implement and industrialize machine learning models into production by utilizing state of the art tools/algorithms and methodologies following DevOps and a test-driven development process, bridge the gap between insight and actions.
Develop scalable and production-ready Advanced Analytics and AI software and products.
Believes in a non-hierarchical culture of collaboration, transparency, safety, and trust with a focus on value creation, growth and serving end-users with full ownership and accountability.
JOB RESPONSIBILITIES:Big Data Specialist
Develop an understanding of business obstacles, objectives and create solutions based on advanced analytics and draw implications for model development
Combine, explore and draw insights from large and complex data assets obtained from different parts of the business.
Design and build explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques
Prototype and pilot new solutions and be a part of the aim of ?productizing and industrializing? those valuable solutions that can have an impact at a global scale
Guides and coaches other chapter colleagues to help solve data/technical problems at an operational level, and in methodologies to help improve development processes
Identifies and interprets trends and patterns in complex data sets to enable the business to make data-driven decisions
Advocate data-driven decision making through for example experimentation and other quantitative analysis
Design advanced analytics solutions together with business stakeholders and product/analytics teams to maximize impact; function as the link and catalyst
Pressure-test algorithms from a business logic perspective and develop value proofs/ business cases
Support in analysis and verification of model output and work with data scientists to improve the accuracy of the model
Analyze data using the latest web analytics and business intelligence techniques
Develop industrialization process to rollout by ensuring real-time data collection across the portfolio
Implement tools (e.g., Power BI or web-analysis dashboards) that help data consumers to extract, analyze, and visualize data faster and better through data pipeline
Design, develop and build real-time data pipelines from a variety of sources (streaming data, APIs, data warehouse, messages etc.)
Leverage the understanding of software architecture and software design patterns to write scalable, maintainable, well-designed and future-proof software
Manage existing pipelines and create new pipelines from a variety of sources (relational, XML, etc.)
Actively apply best practices within CI/CD
Propose and implement solutions for data pipeline stabilization and data quality checks
Coordination with other teams to design optimal patterns for data ingest and egress, as well as lead and coordinate data quality initiatives and troubleshooting
Ensure best practices are followed across architecture, codebase, and configuration
Machine Learning & Artificial Intelligence:??
Test and scale new algorithms through pilots and later industrialize the solutions at scale to the comprehensive fashion network of the Group
Influence, build and maintain the large-scale data infrastructure required for the AI projects, and integrate with external IT infrastructure/service to provide an e2e solution
Leverage an understanding of software architecture and software design patterns to write scalable, maintainable, well-designed and future-proof code
Design, develop and maintain the framework for analytical pipeline
Develop common components to address pain points in machine learning project, like model lifecycle management, feature store and data quality evaluation
Provide input and help implement framework and tools to improve data quality
Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, designers, product
managers and others to build the AI ecosystem within the Group
Deliver on time, demonstrating strong commitment to delivering on the team mission and agreed backlog
