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Kamini GargKG

Average response time: 1 hour

About Kamini

Most organisations are investing in data but struggling to connect it to business outcomes. That's the gap I close.

I am a Fractional Head of Data & AI with 10+ years in data science and analytics across Swiss telco, Fortune 500 consumer health, and global supply chain environments. I work with companies to build data functions that move revenue and reduce costs, without the overhead of a full-time hire.

My track record includes generating CHF 5M in annual incremental revenue through customer segmentation and targeting, reducing customer attrition costs by CHF 2M through predictive modelling, and improving forecast accuracy by 20% across 11 EMEA markets.

I bring both the technical depth to build it — in Python, SQL, ML, and Azure — and the commercial perspective to make sure it matters. I work as an embedded fractional leader, owning the data roadmap, keeping the work connected to what the business is trying to achieve, and getting it done myself.

If your company is sitting on data that isn't yet paying off, that's exactly where I work best.
  • English

    Native or bilingual

  • German

    Basic

Can work on-site
Zurich (up to 50km)

Experience

  • Visthena GmbH, Founder
    Fractional Head of Data & AI
    DIGITAL AND IT
    January 2025 - Today (1 year and 5 months)
    Zürich, Switzerland
    • Diagnosing where revenue is being lost and identifying the data gaps that are making it impossible to act on
    • Translating commercial questions into data requirements: defining what needs to be built, in what order, so the business can start making decisions it currently cannot make
    • Delivering the analytical and technical work directly, in Python, SQL and ML, not just setting the direction but getting it done
    • Owning the data roadmap for leadership teams – setting priorities, removing blockers, and keeping the work connected to decisions that move the business forward
    • Making sure what leadership wants to know and what the data team is actually building are the same thing – so investment goes where it moves the business, not where it's easiest to build
    data strategy Revenue Optimisation Funnel Analytics Python & ML Fractional Leadership
  • Johnson & Johnson / Kenvue
    Senior Data Scientist – Supply Chain
    LOGISTICS AND SUPPLY CHAIN
    November 2021 - March 2024 (2 years and 4 months)
    Zug, Switzerland
    Led the technical delivery of demand sensing across EMEA and India for one of the world's largest consumer health companies.

    • Improved forecast accuracy by 15–20% across 11 EMEA markets, reducing overstock, stockouts, and cost exposure across thousands of SKUs
    • Scaled a demand sensing solution across India covering ~70% of the market, giving regional teams a clearer, more reliable forecast to plan from
    • Built and got into production end-to-end ML pipelines on Azure with sub-hour runtimes, processing demand forecasts across thousands of SKUs within a single planning cycle
    • Served as the main bridge between data science and senior supply chain stakeholders, turning complex ML outputs into decisions leadership could act on
    • Provided technical leadership to a team of 5–6 – data scientists, data engineers, and business analysts — setting direction, reviewing work, and keeping delivery on track
    Supply Chain Analytics Demand Forecasting ML Pipeline Development Cross-functional Leadership Stakeholder Management
  • Sunrise Communications
    Lead Data Scientist
    TELECOMMUNICATIONS
    June 2019 - October 2021 (2 years and 4 months)
    Zürich, Switzerland
    Operated as the most senior data scientist in the Business Intelligence team at one of Switzerland's largest telecommunications providers.
    • Developed a B2C migration strategy generating approximately CHF 5M in annual incremental revenue, built on customer segmentation and targeting models, with a business case presented to the CMO that secured full market rollout
    • Built call volume forecasting models to optimise staffing and reduce cost in customer service
    • Led the B2B analytics value stream as Product Owner, owning use cases across profitability analysis, proces improvement, and commercial performance
    Customer Migration Strategy Revenue Optimisation Churn & Propensity Modelling Data Product Management Predictive Forecasting

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Education

  • PhD in Informatics
    University of Lugano (USI)
    2017
    PhD in Informatics
  • 5-Year Integrated Bachelor & Master in Information Technology
    IIITM
    2009
    5-Year Integrated Bachelor & Master in Information Technology

Skill set

Categories