Holistic tech and data consulting in practice

Take a look at a selection of recent projects in holistic tech and datA transformation. Each one tells a story of success through collaboration, removing silos, and aligning tech and data with strategy.

AI Transformation

in traditional industries

From first proof-of-concepts to value at scale with many AI systems working in production.

Company in the energy utilities industry wanted to set up an AI Center of Excellence to enable AI use cases. I joined as the first AI hire when the company had very low AI maturity.
- Few projects (all done with external partner), fewer deployed.
- Outdated infrastructure and environments (coding platforms reserved only for “real IT”, data scientists relegated to sandbox notebooks). Cloud access limited.
- Lack of buy-in outside of a few front-runner departments.
Set a goal: “everyone is empowered to use AI to get value”.
Holistically developed the company’s AI maturity, focusing simultaneously on:
- People
  - Python training with 100% “would recommend to colleague” rating to drive grassroots demand.
  - AI demystification course and use case workshops for managers to identify high-value use cases.
  - Hiring the right people (business-focused data scientists and ML engineers) to deliver the use cases.
- Tech + Data Stack
  - Worked with IT to get modern data science coding capabilities.
  - Modern ML-Ops deployment made possible.
- Strategy
  - Identified use cases critical to core business goals to increase buy-in. Use of AI in workloads was led by them, not forced on them.
  - Meetups and presentations at conferences helped team gain maturity.
- Technical Product Management
  - Clear service offering for teams interested in AI.
In 2 years, drastic increase in AI maturity.
- Managers proactively identifying AI use cases and making their own AI roadmaps
- 10 ML models in production across 8 departments
- ML proof-of-concepts in 15 departments
- Modern data stack for data scientists
- Team of 20 data scientists and ML engineers working in interdisciplinary teams across the business

data careers

in a changing landscape

Getting more bootcamp participants hired in their dream jobs: better applications, better preparation for technical interviews, and better portfolios.

Young tech and coding bootcamp developed new courses for data science and analytics. They discover that their career support, original developed for software engineering, don’t fit for data roles.
- High-caliber career mentoring process and high placement success for other courses set the bar high
- Extreme rate of change in the wider data career market
- Data career path less established than in other technical careers
Worked with existing careers process and bootcamp curriculum to set individual students up for success in their job search, while giving the bootcamp a sustainable, scalable process
- People
  - Mentored dozens of bootcamp participants one-on-one, helping them optimize their CVs and job search processes to get hired
  - Developed remote career session, given to hundreds of bootcamp participants, on how to prepare for a crucial stage of the data science hiring process: the take-home challenge
- Tech + Data Stack
  - Aligned recommendations in the technical interview session to the stack the participants were working with in the bootcamp to make it user friendly
  - Surveyed data teams in Berlin and wider Europe to track top tools hiring managers sought
- Strategy
  - Helped Head of Career Development understand the data career landscape through interviews and research: what role names mean in different companies, role specialization, hiring decision makers, and how roles differ in companies depending on data maturity of the organization
- Improved hiring support tailored to data roles
- High placement rate for bootcamp graduates lead to recognition by the government employment office and subsidized attendance