Manager, Statistician

Job Description

What Youll Be Doing:

• Own our unified analytics solution by building multi- touch attribution models (MTA) and marketing- mix models (MMM) to address marketing effectiveness, return on investment (ROI), brand equity impact, segmentation, pricing, and environmental factors
  • Build analytic attribution models and marketing mix models using advanced statistics, econometrics, and/or machine learning techniques such as logistic regression, choice model, time- series model, panel data model, Bayesian statistics, ridge regression, structural equations, probability theory, clustering algorithms, decision trees, etc.
  • Quantify the impact of paid media, organic media, web navigations, and individuals propensities on multi- step conversion activities in the consumer journeys
  • Analyze cookie level data sets to generate deep insights on consumer conversion paths related to media overlap, recency, frequency, and targeting
  • Validate the model using statistical diagnostic techniques, attribution results, ROI, forecasting, simulation and optimization
  • Ensure rigorous quality control and detect anomalies in the model with ongoing new data stream
• Collaborate global data science teams to ensure alignment on modeling methodologies, model validation metrics, actionable insights, and analytical/technical best practices, and lead enhancing our analytic solutions for client needs
• Interdisciplinary work: interact with multiple teams across the firm to provide and improve our end- to- end solution and implement new analytics capabilities: Data Operations, Solution Architects, Advisory Services, Product and Engineering
• Mentor or manage junior modelers on a daily basis and develop training programs, while coordinating with cross- functional leads in order to align against broader business objectives and team development

Skills, Talents, Experience You Will Need:

• You will have experience specifically in Algorithmic Attribution or Last Click Attribution, Predictive Models, Marketing Mix Models, Shopping Basket Analysis, Targeting and Next Best Actions.
• Our ideal candidates possess a combination of academic or professional work experience in marketing mix modeling, digital attribution modeling, multivariate regression, time- series modeling, Bayesian statistics, segmentation modeling, machine learning, data mining, simulation, optimization, and/or forecasting
• Technical or programming skills to solve large- scale information, online search, online advertising attribution and online/offline marketing optimization problems
• Experience with Hadoop, Hive, SQL, R, Python, Spark, Matlab or similar is required
• 7 years of quantitative analytics experience with marketing metrics and tracking, marketing analytics, and attribution modeling is highly desirable
• 3- 7 years of work in Digital Analytics with hands- on experience in Adserver/Web Analytics Logs is highly desirable
• 3- 7 years of work in digital AdTech industry with thorough understanding of digital metrics is highly desirable
• Bachelor s degree (required) or above (preferred) with mathematical or engineering background: Statistics, Data Mining, Operations Research, Econometrics, Finance, Engineering or similar
• Ability to communicate well with colleagues from other technical disciplines
• Ability to mentor junior data scientists
• Ability to manage multiple projects with a large cross- functional team
• Strong work ethic with the ability to adapt to the situation, be flexible and nimble in terms of work planning, and to think quickly on your feet

Who You Are:

• ACCOUNTABILITY: Passionate about Customer Success, being accountable to our customers, to our teams, and to ourselves, for doing what it takes to be successful.
• COLLABORATION: Be a team player, always collaborating and working efficiently with members of local and remote teams.
• TRANSPARENCY: Speak with honesty, clarity, brevity, and with purpose. Able to engage with customers and team members of all levels.
• RESILIENCE: Ability to excel in high levels of change, ambiguity, and uncertainty. Continue pushing towards success when working through adaptable situations.
• RESPECT: Be respectful of our customers and our teams. Constructively engage with all partners and work towards success.
• BEGINNERS MIND: Always have a learning mindset and approach to each engagement and problem. Being hands- on and working with others to continue self- development.
• URGENCY: Ability to move fast and drive business values and results for our customers and for Neustar.

Keyskills :
return on investmentmarketing mix modeling panel datapaid media data miningdata science brand equityweb analytics