Arnhem-Nijmegen Region
Seasoned IT professional with a positive look on life. Investigative and enterprising mindset able to produce AI and data driven solutions for business success. Three citizenships: BR; NL; NZ(also Australia). 4 western European languages (PT, EN, ES, NL); w/ basic French comprehension. Generalist professional with decades of experience in IT focused on: AWS Cloud; BI/AI; B2C/Customer Centricity; customer value management. Professionals seeking mentorship: connect to explore opportunities for growth in various areas, I offer insights/mentoring in: AI; IT; Data; AI; financial analytics; data-driven decision making. For those located in NL/BE/Western Germany I can also provide guidance on these that also help work: yoga (teacher diplomed in India, volunteer teacher at my employer); swimming (practice all 4 styles). My training and experience allow me to translate strategy to data-driven IT. Trained and experienced in: 'digital and direct marketing' and management of product; project; process; financial yield; customer value; IT; data. During the last 11 years I have served: marketing agencies; marketing departments of large Companies (Telcos, Banks); startups; and others with varied roles and skills in the following IT verticals: (1). business intelligence (DW/ETL/Data Science); (2). digital and direct marketing (NBA/RTD real time decisioning; omnichannel personalised orchestrated marketing); (3). web/online. With some exception made to some testing, I am a generalist qualified with both experience and training to play a variety of roles: advisor to directors/CXO; enterprise/domain/solution architect; customer intelligence/value/base manager/customer insights manager; marketing operations manager/lead; product manager/owner; business analyst/architect; technical project manager; team lead; senior developer; developer. In my early days I acquired solid computing skills at top world universities, specialising mostly in: software engineering (the whole lifecycle); capacity/performance; data-mining/AI/optimisation; architecture (BPM, EAI, SOA, blueprinting/roadmapping); design thinking. Certifications: CVM = Customer Value Management (Wharton University); Data Management & Data Warehousing (DAMA); Scrum product owner; Scrum master; Java architect; AWS cloud solution architect SAA (& cloud practictioner); Java developer. P ega Certifications (5x omnichannel personalised marketing, BPM): Postgraduate diplomed in direct/digital marketing; MSc in software architectures. Taught corporate courses in the above areas. Contact: [email protected]
Architecting and developing logistics data processing solutions with DBT, data build tool.
I did the data and solution architectures for closed-loop AI that learns from interactions with humans. This article from Harvard Business Review called: “Your Organization is not ready for AI” was released months after we were already practicing most of what it preaches (https://hbr.org/2024/02/your-organization-isnt-designed-to-work-with-genai). The central pieces of what we did was a operational BI/AI data-warehouse. This data-warehouse stored the scores or predictions; decisions or prescriptions; feedback or likes/dislikes and the document data catalogue. Closed-loop AI Example: an email is scored as urgent using NLP; a decision is made to route it to the urgent queue; the CRM agent likes the routing. This AI data-warehouse allowed: continuous improvement; reporting; model tuning/drift analysis; auditability and compliancy to GDPR right of explanation; EU AI Act; other. Techniques were used for fast inserts by expensive GPU machines (messaging; data-vault model making key lookup unnecessary by the use of natural keys for all). Real time Aurora serverless DB interconnected with our business data-warehouse (Redshift) via Zero ETL. Skills: Data Modelling (Data Vault Mostly). Specifying data processing pipelines, lineage, etc (using data flow diagrams). AWS Cloud (Lambdas, S3, Redshift, Aurora Serverless). Time series forecasting for customer and finance data (using Deep Learning; XGBoost). Most of the natural language work was done by the squads, but I did prototype named entity recognition; summarization/classification of text; etc. SNS/SQS.
Insurance Data Architect for Partenamut (Top employer 2023 Belgium). Managing the data-manager and data management function. Reporting to Analytics Director/CDO. Key resp.: privacy by design. Structured our Document/NLP data lake and tabular data lake. Delivered solutions for employee/customer-centric projects (single views; combined solution for experimentation+control-groups+A/B testing; data quality monitoring; processing clickstream/web-Analytics ourselves). Delivered policies/specifications/solutions for pseudonymization; anonymization; NLP document redaction/NER (named entity recognition). Recommended anonymization solution for shared data pooling superior to single keyed hashing and less costly than zero-party computation. Alignment with DPO; security; risk; IT; Data Eng.; Data Sci. Defined data protection related processes such as access controls (DMBOK certified). Prepared-for and responded-to audits. Defined software lifecycle best practices, with regards to data, privacy. Evangelization. Coordinated technical change across data-science and data engineering teams for FAIR data and serverless/microservice based architecture. Generated data models: conceptual; logical (data-vault; dimensional; data marts). Types of data marts: customer analytical records and other such as prospect analytical record; case analytical record; also in real-time. Bridging architecture to development. Constructed simple marketing automation and next-best action systems reusing Amazon AWS data infrastructure and Tealium activation (similar to AWS SES and AWS Pinpoint). Elaboration of the processes/architecture for GDPR Consent Management/Privacy by design/Privacy management. Procuring data catalogue. AI CRM ticket routing to max customer satisfaction and resolution time. Architecture and prototyping in AWS: Aurora Serverless; Redshift; SNS/SQS; Lambda functions (also in Docker containers); Step Functions; Sagemaker; CDK w/ Python CI/CD; Secret Manager; Dynamo; guardrails.
Working with product owners and delivery management on simplified agile at scale trio (Spotify model). Providing engineering solutions to business problems. Objectives/goals: data-driven omnichannel marketing; customer-centricity; marketing relevance; personalisation; customer value management. Integrating various technologies: [1] Data warehouses/data lake (D atabricks; S ynapse); [2] near real-time customer-analytical-records (near-real-time =~ active data warehousing and customer analytical records =~ spine-tables; mining-tables; single views of the customer/subject) and NBA Next-best-action/closed-loop-marketing/decisioning (P ega Marketing); AI (A zure Machine Learning); [3] optimization/experimentation (e.g. Split IO, MMO or marketing mix optimization; control groups; universal experimentation w/ multiple systems seeing the same segments/splits); [4] Campaign management (P ega); [5] Web Analytics / Advertisement (Google analytics; Google Ads); [6] Paid Media Marketing (Salesforce Audience Studio; P ega Paid Media; Facebook & Google Ads-managers); [7] Portals; (Java, Javascript, Web Cache and Profiles in Cosmos DB; Graph QL); [8] Feedback tools (e.g. Usabilla); [9] Some architectures in A zure Event Streaming; other messaging or streaming systems (Kafka). Architected data solutions in A zure using both UML and TOGAF/Aris/Archimate. Did a business process and functional decomposition of marketing/CDM (customer data mgmt) bus. area. Coded extensively in A zure at home. A zure trainings (Z 90 0; D P200; etc). Read at least one book each for: D atabricks; A zure ML; S ynapse. That on top of previous experience leading the construction of 3 data warehouses (in Oracle; PostgreSQL and some M S T-SQL); and Dama Dmbok data mgmt. Architected for a combination of data lake and S ynapse (DW). With ingestion resembling some aspects of data vault modelling (at least for the load_date; conformed business keys). Governance/privacy/pseudonymization/anonymization/policies.
2017, 2018, 2019: Dedicated to business analysis, requirements and training/coaching of staff at individual and group level (> 50% of the time). Drove the decisioning, customer value management; scientific data-driven marketing (control groups; champion and challenger; AB testing optimisations) first implementations of omnichannel real-time marketing for 4 Vodafone Opcos (in 2 as P ega.com badged consultant). Including projects for learning from purchases as opposed to proposition accept or clicks. My care for Vodafone customer became evident to all (I was myself Vodafone employee in its initial years from 2003 to 08). 2016, 2017 Managing; coaching; architecting and delivering P ega Marketing solutions for 2 insurance companies (2 companies). In the first insurance company (Achmea) contracted via P ega.com themselves as a P ega marketing project coach, Lead decisioning architect. The context of this coaching: (1). the only person experienced in Pega marketing in the project; (2). coaching and training a team of more than 10 people that are certified/but not experienced yet in P ega marketing (getting the experience now); (3). utilizing high-quality material I developed that complements the P ega training. (4). deliverables highly focused in personalisation, architected a personalised newsletter with each piece of news tailored and selected based on reader behaviour. (5). Trained business stakeholders on using creative proposition marketing. (6). Trained the data department on high value customer analytical records. In the second insurance company (DEVK) we focused mostly on marketing automation. Responsible for full planning of project activities to integrate P ega field marketing with external B2B insurance sales intermediaries and DialogWorks API for email marketing. After planning I led some development. On my spare time: applying LTSM deep neural nets and XGBoost to time series prediction; regression. See coaching example below:
2019 Lead Decisioning Archiect for Vodafone Portugal (using P ega 8.1 for data-driven NBA/Marketing). Starting the omnichannel programme with real-time triggered outbound campaigns for retention (part of "always-on" marketing programme). On a P egaSystems contract. At that time I was the only external doing Pega marketing. Presentations and trainings given on reporting capabilities within P ega marketing. 2018 LDA (lead decisioning architect) for the CVM (Customer Value Management) department from Vodafone Netherlands. P ega Marketing 7.3. Built the foundation for the "always-on" marketing programme. Contracted via Pega.com for customer. One of two external consultants in the project (my responsibility: Pega marketing; his responsibility: infra and cloud). Deliveries: (1). Presentations and training for building awareness of new ways of doing marketing for digital transformation; (2). green field building of omnichannel marketing platform infrastructure; (3). centre of excellence/best practices on regression testing; (4). training on extracting value from data by designing a good customer analytical record/spine table/mining table for the 360 view of the customer, together with effective use of the customer interaction history; (5). consulting on several areas: journey management, multi-channel media neutral marketing, digital transformation and marketing + marketing operation processes. (6). Coaching of internal marketing staff; advising managers (more than 30 hours of presentations given on competitiveness; omnichannel marketing; experimental marketing/champion and challenger/control groups; migration from U nica outbound to P ega; CVM; etc).
MerkleInc: largest independent data analytics, CRM & performance marketing agency in the US, Merkle. Largest independent CRM agency in Europe. Dentsu Aegis: 5th largest marketing group in the world. Jul-Aug 2016: SDA, senior decisioning architect for an NBA, RTD (real time decisioning) project for HSBC bank Australia (working as P ega.com staff and joint with the largest P ega partner). Responsible for business analysis and implementation of prioritisation strategies; responsible for design and implementation of: validity/eligibility; contact and treatment; real time adaptive models for both propositions and the choice of their treatments. P ega marketing 7.2. Omni-channel. 2014-2015: Product owner-PO for a GUI Front-end to SAS.COM customer intelligence system (SAS marketing automation). Project: creating a Java web front-end for geofencing marketing targeting (define campaign and its geofence). Team: ~3 Java; basic Spring developers. Customer: our director and SAS.com itself (2 director level stakeholders). Methodology: scrum/agile. Delivery platform: Amazon AWS EC2 and S3. Mar-Jun 2016: Finishing my marketing diploma; doing thought leadership; writing business process for our line of work; certifying as P ega SDA; preparing for other certifications.
Aug15-Mar2016: Pega Senior Decisioning Architect/Consultant. End-to-end role responsible for: business analysis; architecture; design and implementation of most of the marketing decisioning strategies: retention; omnichannel (centralised decisioning inbound+outbound marketing automation); customer value management/CVM retention calculators; contact and treatment frameworks; product compatibility; offer compatibility; etc. Customer is Wind Telecom in Milan, subsidiary of Vimpelcom the 6th largest Telco group. The project was a greenfield NBA project. Reporting to Pega Technical Director. Project joint with another large Pega partner. Software: Pega 7.1.12, mostly strategy designer. Jan14-Aug15: Pega SDA Senior Decisioning Consultant. part Merkle's team doing Pega centralised decisioning/next best action marketing at two Scottish banks and one UK telecom. For the two Scottish banks I joined the Mobile-First B project for Clydesdale and Yorkshire Banks (https://mobilemarketingmagazine.com/mobile-first-b-takes-flight-clydesdale-yorkshire-banks); reporting to diverse team leads on a project joint with one of the largest Pega partners. For the British Telecom, I looked business analysis for a project to allow tablet point of sale decisioning with artificial intelligence to support the work of telecom physical shop staff (e.g. recommend on tablet screen the best mobile and price plans based on AI). Nov13-Nov14: Product owner / Scrum master coach on project creating a self service digital marketing agency front-end to SAS IA/AIMatch. Technologies used: Java/JEE (Restful; JAXB, JSON, Knockout.js, AJAX, XSLT); deployed to Amazon Cloud/AWS with EC2; Beanstalk. Led three people in my team. Reporting to SAS.com. Sep13-Nov13: Digital/Direct Marketing+IT Consultant in international projects (weve.com, monitise.com) involving BI, Web and Performance applied to direct marketing and online advertisement.