Data Science Specialist - Bengaluru, India - Applicantz

    Applicantz
    Default job background
    Technology / Internet
    Description

    THIS IS A LONG TERM CONTRACT POSITION WITH ONE OF THE LARGEST, GLOBAL, TECHNOLOGY LEADER.

    Our large, Fortune client is ranked as one of the best companies to work with, in the world. The client fosters progressive culture, creativity, and a Flexible work environment. They use cutting-edge technologies to keep themselves ahead of the curve. Diversity in all aspects is respected. Integrity, experience, honesty, people, humanity, and passion for excellence are some other adjectives that define this global technology leader.

    Qualifications:

    • 3+ years of proven experience in the Marketing domain, especially in applying data science techniques to marketing problems.
    • Proficiency in Python, SQL, and Snowflake.
    • Solid knowledge of standard probability distributions and statistical tests.
    • Previous experience with machine learning techniques related to classification, regression, and clustering.
    • Familiarity with A/B testing, Attribution, Time series projection, Linear programing/Optimization.
    • Ability to communicate clearly and effectively with stakeholders at all levels of the business.
    • Able to apply machine learning techniques for classification, regression, and clustering to derive insights from complex data sets
    • Degree in Computer Science, Statistics, Mathematics or a related field.

    Responsibilities:

    • Design and implement A/B testing procedures to understand the impact of various marketing strategies.
    • Develop and maintain attribution models to identify the sequence of touchpoints that lead to a desired outcome.
    • Use time series projection and linear programming/optimization techniques to forecast marketing trends.
    • Apply machine learning techniques for classification, regression, and clustering to derive insights from complex data sets.
    • Build and refine scoring models for accounts and leads to drive more efficient marketing spend.