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Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.

Auteur(s): Dr Genevieve Hayes
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À propos de cet audio

Are you tired of spending hours mastering the latest data science techniques, only to struggle translating your brilliant models into brilliant paychecks? It’s time to debug your career with Value Driven Data Science. This isn’t your average tech podcast – it’s a weekly masterclass on turning data skills into serious clout, cash and career freedom. Each episode, your host Dr Genevieve Hayes chats with data pros who offer no-nonsense advice on: • Creating data solutions that bosses can’t ignore; • Bridging the gap between data geeks and decision-makers; • Charting your own course in the data science world; • Becoming the go-to data expert everyone wants to work with; and • Transforming from data scientist to successful datapreneur. Whether you’re eyeing the corner office or sketching out your data venture on your lunch break, Value Driven Data Science is here to help you rewrite your career algorithm. From algorithms to autonomy - it's time to drive your value in data science.© 2025 Genevieve Hayes Consulting Économie
Épisodes
  • Episode 89: [Value Boost] LinkedIn Strategies for Boosting Your Data Science Career
    Nov 19 2025

    LinkedIn has become a powerful career tool for data scientists willing to invest the time. Regular posting can lead to unexpected work opportunities, reconnections with former colleagues, and valuable networking with professionals worldwide. But making the leap from occasional posting to consistent content creation can feel overwhelming.

    In this Value Boost episode, Sarah Burnett joins Dr. Genevieve Hayes to share practical LinkedIn strategies that can transform your data science career.

    In this episode, you'll discover:

    1. How Sarah went from posting twice a year to daily LinkedIn content [01:25]
    2. The biggest benefits of consistent LinkedIn posting for data science careers [03:15]
    3. How to manage the challenge of daily content creation without burnout [04:31]
    4. The one LinkedIn strategy every data scientist should start using tomorrow [08:47]

    Guest Bio

    Sarah Burnett is the co-founder of Dub Dub Data, a consultancy that offers human-centric AI and Tableau solutions. She transitioned into independent consulting after navigating redundancy from a senior role at a major bank. She is also the co-host of the podcast unDubbed.

    Links

    • Connect with Sarah on LinkedIn
    • Dub Dub Data Website
    • Connect with Genevieve on LinkedIn
    • Be among the first to hear about the release of each new podcast episode by signing up HERE
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    10 min
  • Episode 88: Building a Data Science Career After Unexpected Job Loss
    Nov 12 2025

    There was once a time, when data science was still in its infancy, when demonstrating any attempt to learn Python or machine learning was enough to secure a job interview. The demand for data scientists massively outweighed supply.

    Ten years later, however, the job market has dramatically shifted - and many data scientists who unexpectedly find themselves out of work face a truly overwhelming experience.

    In this episode, Sarah Burnett joins Dr. Genevieve Hayes to share how she transformed redundancy from a senior banking role into the launch of her own successful data consultancy, proving that unexpected job loss doesn't have to mean career disaster.

    In this episode, we explore:

    1. Why redundancy is a numbers game, not personal failure [03:54]
    2. The power of taking time to process after job loss, instead of rushing back [08:47]
    3. How to pivot when your first business idea doesn't work [16:58]
    4. Why building side projects and community involvement create career insurance [20:52]

    Guest Bio

    Sarah Burnett is the co-founder of Dub Dub Data, a consultancy that offers human-centric AI and Tableau solutions. She transitioned into independent consulting after navigating redundancy from a senior role at a major bank. She is also the co-host of the podcast unDubbed.

    Links

    • Connect with Sarah on LinkedIn
    • Dub Dub Data Website
    • Connect with Genevieve on LinkedIn
    • Be among the first to hear about the release of each new podcast episode by signing up HERE
    Voir plus Voir moins
    27 min
  • Episode 87: [Value Boost] How Your Weirdness Could Be Your Data Science Superpower
    Nov 5 2025

    When most data scientists think about their competitive edge, they focus solely on what goes on their resume - education, work experience, and technical skills. But what if the things that truly make you irreplaceable go far deeper than your LinkedIn profile?

    Your family background, cultural influences, communication quirks, and even the hobbies that make you nerd out all contribute to what makes you uniquely valuable.

    In this Value Boost episode, Danny Ruspandini joins Dr. Genevieve Hayes to explore the concept of your "untouchable advantage" - the unique combination of experiences and qualities that make you impossible to replace as a data scientist.

    You'll discover:

    1. Why your untouchable advantage extends far beyond your technical qualifications [02:09]
    2. How family influences and personal quirks become professional superpowers [04:14]
    3. Why introverts have unique advantages they often don't recognize [10:36]
    4. The simple way to uncover your own untouchable advantage starting tomorrow [14:08]

    Guest Bio

    Danny Ruspandini is a brand strategist, business coach and director of Impact Labs Australia. He is also the creator of One Shiny Object, a program for helping solo creatives package what they do into sellable, fixed-price services.

    Links

    • Connect with Danny on LinkedIn
    • Download the One Shiny Object framework
    • Connect with Genevieve on LinkedIn
    • Be among the first to hear about the release of each new podcast episode by signing up HERE
    Voir plus Voir moins
    16 min
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