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Decision Scientist, WhatsApp 321 views

Are you passionate about WhatsApp? Are you excited about Marketing, both brand, and performance? Do you thrive at the intersection of data science, consumer actions, sentiments, marketing, and product? Do you have an insatiable curiosity to understand what messages resonate with which users? Do you have experience in launching hypothesis-driven experiments, provide data-based insights to help marketers make better decisions? Do you have an urge to challenge the status quo and own improving it? Do you bring positive energy to help the teams you belong to? Do you have empathy for business users who may not be as data-savvy as you are? Are you strong in quantitative, analytical thinking and technical skills (SQL, Stats, R/Python, etc.)? Are you hungry to create impact by owning and driving analytical projects? If Yes to most of these questions, let’s talk.

Responsibilities

  • Influence the brand marketing and media strategy by developing a deep audience understanding by integrating consumer perception, sentiment, and product behavioral data and translate them into recommendations and actions
  • Develop marketing measurement plans, learning agendas, metrics and goals that echo the brand and marketing strategy. Socialize the plan with cross-functional partners (marketing, research, media, product) and gain alignment.
  • Execute marketing surveys via in-house tools and vendors to get a robust read on consumer sentiment.
  • Study the performance of marketing campaigns using robust and state of the art measurement techniques, statistical or econometric models and ensure accountability of marketing.
  • Optimize media mix on digital channels (Google, Facebook, Programmatic) and offline channels (TV, Radio, OOH, etc.) by executing experiments and lead the test-learn-optimize cycle with our media partners.
  • Develop quantitative and analysis, tools, and models to support marketing decision making. Analytical areas might include (but not limited to): audience segmentation, A/B, multivariate experimental design and hypothesis testing, media mix modeling, marketing optimization, advanced survey analysis, text mining, regressions and measurement sciences (causal inference, observational data analysis, bias mitigation, matching techniques, etc.).
  • Produce clearly written narratives, documents, and decks that include data visualizations such as charts, infographic, and dashboards to communicate measurement plans, findings, caveats and actionable recommendations to cross-functional stakeholders

Minimum Qualification

  • A degree in economics, econometrics, operations research, mathematics, statistics, engineering, psychology, business, or another field with quantitative roots and demands
  • 3+ years of experience in data analysis, data science, marketing analytics, or similar quantitative fields, applying experimentation methods to test various hypotheses for various marketing outcomes such as customer segmentation, causal marketing measurement, and media optimization.
  • Statistical or econometric modeling or marketing analytics (e.g. experimental design., significance testing, media effects, media mix modeling, marketing optimization, econometric methods, observational data, causal inference, regression modeling, sampling theory, etc.)
  • Experience using R or Python or Stata or a similar scripting language for statistical or econometric modeling.
  • Experience with SQL, Hive, Presto, Hadoop, or other data querying languages
  • Experience communicating with cross-functional stakeholders including brand strategists, market researchers, product marketers, creative directors, media planners, and engineers.
  • Strong time management and communication skills are critical. Experience in written communication, writing documents to articulate analytical plans, laying out hypotheses and summarizing results into succinct recommendations.

Preferred Qualification

  • A Master’s or Doctorate degree in economics, econometrics, operational research, mathematics, statistics, engineering, psychology, or another field, or an MBA with quantitative marketing, consumer research focus.
  • Management consulting experience or a similar career requiring one to present data-driven insights to business audiences
  • Experience using open-source statistical packages such as dplyr, Rstudio, NumPy, Pandas

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