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The Manager of Machine Learing & Operational Analytics for Wolters Kluwer (WK) Governance Risk & Compliance (GRC) is responsible for developing & implement machine learning solutions for operational processes or otherwise, establishing structured project engagement with business unit leaders, analytics driven business transformation and new innovative solutions of process and technology to significantly drive core operational improvements in GRC.
The position is expected to be comfortable with modern day data science tool and continuously learn new tools and techniques to enhance productivity and profitability.
Manager is a hands-on role establishing structured project engagement with business unit leaders, analytics driven business transformation and new innovative solutions of process and technology to significantly drive core operational improvements in GRC. Manager will drive excellent framing and communication of his ideas to executive leadership using compelling quantitative and qualitative reasoning to drive case for change for the organization. The Manager will be self-motivated to work independently and in collaboration with key internal team members (e.g., General Managers, functional leaders, process owners) across the organization with different collaborative styles. The Manager drives the analytical evaluation of existing processes and the development of plans to improve processes across the entire organization. Manager will create program/project management structures to drive the discovery, design and implementation of multiple solutions that leverages best practices in the industry and innovative thinking in how to use analytics to drive business outcome. The Manager should be able to analyze operational environments at a detailed level to bring forth new ideas and also be able to proactively address roadblocks to change. Ability to communicate using professional PowerPoint slides, backed up by rigorous factual details including operational pain points, efficiency levers and impacts to customers, employees and shareholders. This is an individual contributor role and it is expected that the person will be doing a large portion of the work independently. Activities of the Manager of Operational Excellence include: creating visibility into key processes; driving the development of improvement initiatives across the entire GRC organization; co-leading the implementation of improvement initiatives across GRC; continuously measuring and monitoring key processes, risks and controls; vendor professionals; participating in organizational activities to meet or exceed company objectives; and representing Wolters Kluwer within the industry.
Essential Duties and responsibilities
- Works to analyze operations using a combination of analytical skills and process understanding. Extremely comfortable in manipulating large quantities of information/data to bring out operational insights like quality, cycle time, cost, variations, bottlenecks, risks, cost-revenue connections and cause-effect analysis. Relate the analysis to impacts for customer, employees and shareholders.
- Works to present insights to engage the organization to drive change. Appreciating the importance of creating an impactful presentation and dialogue to highlight the value of the analysis, impact of recommendation and bring the organization along the transformation journey.
- Project manage the discovery and implementation of transformation journey by creating a clear framework and governance for all level of the organization. Project manage pilots or proof of concept ideas to prove out the hypothesis and ensure that adoption of the change is institutionalized within the organizations.
- Works to create visibility into key GRC processes by understanding the operational footprint of GRC (e.g., operational processes, customer touch-points); driving the development of comprehensive process maps to document baseline workflow (e.g., inputs, critical activities, outputs); establishing metrics and collecting data to fully assess operational and functional processes (business units and corporate-wide); identifying process issues/opportunities (e.g., process gaps, customer service gaps, cost benefit opportunities); collaborating with GRC business units and process owners to review and discuss process issues; and partnering with GRC business units to identify primary risks, risk appetite and controls used to proactively manage risk.
- Drives improvement initiatives across the entire GRC organization by developing and maintaining relationships with leaders, stakeholders and industry experts (e.g., General Managers, process owners, customers); keeping abreast to new technologies and processes within the industry; creating and maintaining a six sigma discipline within the organization; managing the development of process re-engineering plans and/or the mapping of potential improvements for future-state processes and policies; driving full due diligence to determine the pros, cons, costs and savings for future-state processes; overseeing the identification of steps needed to complete improvement initiatives; documenting and/or reviewing project plans (e.g., scope, schedule, budget, staffing); and obtaining buy in from leaders and stakeholders (e.g., management, process owners, functional leaders).
- Co-leads with business the implementation of improvement initiatives across GRC by bringing project plans to business/functional leaders to implement; partnering with process owners and business teams to initiate change initiatives; interacting with leadership throughout implementation to provide guidance and ensure project priorities consistently align with the overall corporate business strategy; recommending control enhancements to mitigate areas of risk that might arise from inadequate or failed internal processes, people or technology; and following up to ensure changes have been thoroughly and effectively implemented.
- Continuously measures and monitors key processes, risks and controls by conducting post-implementation reviews and project follow-up; ensuring process improvements have achieved their designed objective; developing and implementing the collection of metrics to continuously monitor and evaluate processes and key touch points (e.g., effectiveness, efficiency); collaborating with process owners to discuss successes, failures and gaps; ensuring there is accountability where processes are failing to meet expectations; reporting on voice of the process, operational risk and control data; replicating and deploying best practices and processes across the organization; and driving positive change through continuous improvement efforts in key areas.
- Participates in organizational activities to meet or exceed company objectives by applying subject matter expertise to special projects that will help drive profitability and growth; participating in thought provoking, strategic discussions with executive leadership; sharing analytical, quantitative, and conceptual insights to enhance the organization; sharing insight with other leaders regarding team/department operation (e.g., performance management, strategies, company policies and procedures); identifying opportunities to collaborate across divisions and/or leverage partnerships; collaborating with peers to develop and advance company-wide initiatives and strategies; participating as a functional member of WK committees; and serving as a key business leader, thought leader, and role model within the organization
Proactively pursues professional development activities (e.g., establishing personal networks).
- Willingness to participate and contribute in continuous learning initiatives to stay updated with modern technological changes in Data science and Machine Learning
- Manages time and company resources appropriately and maintain data science technology stack
- Performs other duties as requested by the Director of Machine Learning and Operational Analytics
Minimum: Master’s Degree in Operations Risk, Operations Research, Statistics, Economics, Market Research, Engineering, Computer Science, or related field; OR, if no degree, 6 years of experience managing transformational change projects.
Preferred: Working knowledge of Big data platforms
Minimum: 4-6 years of experience managing machine learning projects and implementations
- Working knowledge of SAS, R, Python and willingness to learm big data technologies
- Knowledge and experience of machine learning algorithms is preferred
- Experience with Spark, Scala and Hadoop is a must for this position
- Communicating recommendations and influencing stakeholders through analytics and process knowledge.
- Experience in managing transformational projects
- 3-4 years of significant experience in manipulating large data sets to create insights
- 3-4 years of hands on research and implementation work.
- 3-4 most recent years in strong presentation creation skills
- 4 years working in the financial services or related industry undergoing transformational change
- 4 years of data analytics of operational, revenue or financial data
- 4 years leading positive change in process management, operational risk and controls.
- Demonstrating expertise in six sigma, lean, or similar process re-engineering practices.
- Mapping processes.
- Defining and analyzing issues.
- Performing significant research and coalescing disparate information.
- Managing cross-functional process improvement initiatives.
- Developing relationships at all levels of an organization (including C-level executives).
- Demonstrating strong analytical and problem solving skills.
- Demonstrating organization, time management, and multi-tasking skills.
- Demonstrating excellent written and verbal communication.
Preferred: 4-6 years of experience managing transformational change projects, including:
Expert in PowerPoint presentation creation
- Expert in Excel
- Experience in data analysis and visual tools like SAS or Tableau
- Utilizing Microsoft Visio.
- Utilizing Microsoft Project.
Manager - Data Science at Wolters Kluwer with 10+ years of experience