Anushka Sharma

Cloud & Infrastructure Services | Technology Strategy | Market Intelligence & Advisory | IT Services Research | Digital Transformation

Greater Delhi Area

About

I decode the evolving world of Cloud & Infrastructure Services ☁️ Working at the intersection of technology, strategy, and market intelligence, I analyze cloud ecosystems, IT services trends, and provider landscapes to turn complex industry shifts into actionable insights. Curious about hyperscalers, digital transformation, and the evolving relationship between technology, business, public policy, and governance, and how these forces shape the future.

Experience

  • Everest Group (Full-time · 2 yrs 3 mos)
    • Senior Analyst
      Jul 2022 - Aug 2023 · 1 yr 2 mos

    • Analyst
      Jun 2021 - Jul 2022 · 1 yr 2 mos

  • DTU Times (3 yrs 9 mos)
    • Managing Editor
      2020 - Jun 2021 · 1 yr 6 mos

    • Assistant Editor
      Aug 2018 - Jun 2020 · 1 yr 11 mos

      I've been writing poems and articles on current affairs and theme based topics for DTU Times for about 1.5 years now. As an assistant editor I am responsible for overlooking the day to day coverage process, along with editing the content that goes into our Editions that come out quarterly.

    • Columnist
      Oct 2017 - Aug 2018 · 11 mos

  • Rotaract Club of DTU (3 yrs 11 mos)
    • Club Facilitator
      Jun 2019 - Jun 2021 · 2 yrs 1 mo

    • Animal Welfare Team Head
      Oct 2018 - Jun 2021 · 2 yrs 9 mos

      We take up initiatives wherein we feed our campus dogs and try to get them the required medical attention, if any.

    • Director of Meets
      Jul 2018 - Jun 2020 · 2 yrs

  • International Organisation of Software Developers (3 yrs 11 mos)
    • Head Of Media
      Jul 2018 - Jun 2021 · 3 yrs

    • Member
      Aug 2017 - Jul 2018 · 1 yr

  • Machine Learning Summer Intern at IIT Delhi
    Jun 2019 - Jul 2020 · 1 yr 2 mos

    Worked on Credit Card Fraud Detection Project using Ensemble Neural Networks; Stacking and Voting were the two kinds used. Since the dataset was too large, used data balancing techniques such as undersampling and oversampling in 4 ratios, creating a total of 240 datasets. Applied non-parametric statistical tests namely Anderson-Darling and Kolmogorov-Smirnov tests to ensure the data was normalized. Used clustering on undersampled datasets to compare the results of supervised and unsupervise learning techniques.