AVP, Digital Analytics

VP - Payment Analytics

AVP – Model Ops Engineer

Product Manager

Responsibilities: <ul><li>Lead and deliver Digital Measurement Analytics for Digital Platforms in Agile methodology to drive digital data strategy that includes collection &amp; validation of data and reporting.</li><li>Partner with onsite Stakeholders and various process owners in marketing, technology and digital teams to plan and implement strategic priorities.</li><li>Present analytical results and actionable recommendations to key stakeholders on a recurring cadence, and propose innovative analytics solutions to drive business growth and enhance the customer experience.</li><li>Responsible for team’s effective communication, project deliverables, coaching team on adhering to expected timelines, accuracy &amp; compliance with meticulous project management.</li><li>Lead internal initiatives, perform other duties and/or special projects, as assigned.</li></ul> Requirements: <ul><li>Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 4+ years of hands-on relevant Analytics experience.</li><li>Minimum 6+ years of relevant work experience in lieu of specified degree.</li><li>2+ years of experience in Digital or Web Analytics Domain utilizing tools such as Adobe or Google Analytics and 2+ years of experience in SAS or SQL.</li><li>1+ years of Experience in Managing People, Coordinating work, Supervising, Evaluating performance and ensuring employees are trained.</li><li>Minimum 1+ years of experience in Data visualizations tools such as Tableau to drive insights.</li><li>Excellent oral and written communication skills with ability to collaborate, articulate and present solutions cutting across functional/agile teams in a simple yet compelling manner</li></ul>

Responsibilities: <ul><li>Develop and execute a clear, actionable, and time-bound analytics roadmap, outlining key milestones, resources, and timelines to achieve payment analytics objectives.</li><li>Lead the design and delivery of comprehensive analytics across all payment channels, products, and features, providing end-to-end visibility into the payment lifecycle.</li><li>Identify, assess, and bridge data gaps by collaborating with business, technology, operations, and data engineering teams to ensure complete, accurate, and timely payment data capture.</li><li>Translate complex payment data into actionable insights and strategic recommendations that optimize the payment process, improve customer experience, and drive business growth.</li><li>Partner closely with Tech &amp; Ops Payments, Product Analytics, Payment Train, Customer Experience, and other key stakeholders to embed analytics into decision-making at all levels.</li><li>Build, mentor, and manage a high-performing analytics team, fostering a culture of innovation, accountability, and continuous learning.</li><li>Cultivate and maintain strong relationships across teams to effectively communicate analytics value and drive enterprise-wide adoption.</li><li>Support regulatory review and governance</li><li>Promote advanced analytics practices, including proof-of-concept initiatives, to keep the organization at the forefront of payment analytics capabilities.</li><li>Lead internal initiatives, perform other duties and/or special projects, as assigned</li></ul> Requirements: <ul><li>Degree in Statistics, Mathematics, Economics, Engineering, or any other quantitative streams with 10+ years of hands-on relevant analytics/data science experience, or in lieu of a degree 12+ years of relevant analytics/data science experience.</li><li>8+ years of hands-on Experience in SQL /SAS with proven ability to leverage advanced algorithms and be efficient in handling complex/large data;</li><li>3+ years of experience in BI tools, e.g. Tableau etc.</li><li>5+ years of experience in managing teams with ability to motivate team, drive change, create a culture of learning, innovation and recognition</li><li>Ability to solve complex technical and people-oriented problems with minimal supervision</li><li>Advanced proficiency in MS-Excel and MS-PowerPoint with superior data analyses and story boarding skills</li><li>Strong written/oral communication &amp; stakeholder management skills</li></ul>

Responsibilities: <ul><li>Design, develop, and maintain robust pipelines to collect, transform, and store data used in model monitoring workflows (e.g., scoring data, performance metrics, outcomes).</li><li>Build scalable data architectures to support real-time and batch monitoring, including data ingestion, enrichment, and retention practices.</li><li>Develop reusable monitoring components (e.g., performance drift detectors, threshold-based alerts, metric repositories) that support various model types and regulatory needs.</li><li>Integrate data pipelines with model lifecycle platforms, MLOps tools, and observability solutions to ensure seamless model performance tracking.</li><li>Partner with model risk and compliance teams to ensure data lineage, audit trails, and documentation are preserved and accessible for regulatory reviews (e.g., SR 11-7 compliance).</li><li>Collaborate with data scientists, model validators, and product managers to align monitoring data infrastructure with evolving model monitoring requirements.</li><li>Work closely with the model monitoring analytics and strategy monitoring analytics teams within MO&amp;A to ensure the monitoring data infrastructure adapts to changing analytics and monitoring needs. Enable visualization and reporting capabilities through dashboards (e.g., Power BI, Tableau) that summarize model health, stability, and issue alerts.</li><li>Designing and maintaining high-performance data pipelines that ingest, transform, and version datasets for Model and Strategy Monitoring</li><li>Optimize data storage and compute performance for large-scale monitoring use cases involving high-frequency scoring or model ensembles.</li></ul> Requirements: <ul><li>Bachelor’s degree in a quantitative, technical, or data-focused field (e.g., Statistics, Mathematics, Computer Science, Data Science, Engineering) with 5+ years’ experience or in lieu of degree, and 7+ years of relevant work experience in, data engineering or related roles in the financial services or regulated analytics domain.</li><li>Strong proficiency with data engineering tools and frameworks (e.g., Apache Spark, Airflow, Kafka, dbt, PySpark).</li><li>Proficient in programming languages such as SAS, Python, and SQL for building monitoring pipelines and validation checks.</li><li>Experience with cloud-based data infrastructure (e.g., AWS, Azure, GCP) and data warehousing (e.g., Snowflake, Redshift, BigQuery).</li><li>Familiarity with MLOps practices, model metadata tracking (e.g., MLflow), and monitoring toolkits (e.g., Evidently AI, Why Labs, Prometheus).</li><li>Understanding of model risk governance requirements and the role of data engineering in ensuring compliant model monitoring.</li><li>Ability to work in an agile environment and deliver high-quality, production-grade code in collaboration with DevOps and platform engineering teams.</li></ul>

Responsibilities: <ul><li>Managing portfolio of vulcanized gates, spare gates and kit plates for IDM/OEMs- accommodate the project managers during the stage-gate-process in front of supervisory board meetings, provide documentation and business case background for selected customer projects Improve Costs and process</li><li>Lead the development and implementation of a comprehensive global strategy for managing the obsolescence of elastomers across global organisation</li><li>Supervising all changes regarding supply chain, manufacturing and assembly processes and preparing documentation for customer relevant changes</li><li>Supporting BU GSE and Sales Team with regards to all technical &amp; commercial &amp; operational aspects of gates (product data sheets, product presentation etc.)</li><li>Forecast sales objectives and ensure they are fulfilled by the business development PMs.</li><li>Managing profitability targets for the dedicated gates&nbsp;</li><li>Support other team members (OEM PMs, supply-chain management/project management) throughout the whole process of logistics, delivery, to ensure full customer satisfaction. (after the project acceptance has been confirmed by the customer, operations departments will take responsibility)</li><li>Technical customer documentation like manuals, product data sheets according to European machinery directive for kit plates, gates</li></ul> Requirements: <ul><li>Bachelor/master’s degree in mechanical engineering or related field, preferably chemical engineering&nbsp;</li><li>Experience 8-12 years</li><li>Background or experience in material sciences, preferably within the elastomer &amp; polymer field&nbsp;</li><li>Knowledge and experience in vacuum technology</li><li>Written &amp; verbal communication in German, Mandarin, Japanese or Korean besides English language (added advantage).</li><li>Experience in developing new product and service solutions in a high-tech environment.</li><li>Developing concepts and solutions for the delivery of service products engaging engineering and operations.</li><li>Driving the promotion and roll-out of new products.</li></ul>

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AVP, Digital Analytics

VP - Payment Analytics

AVP – Model Ops Engineer

Product Manager

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AVP, Digital Analytics

VP - Payment Analytics

AVP – Model Ops Engineer

Product Manager

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