Lead Data Scientist

• Work with practice leaders and clients to understand business problems, industry context, data sources, potential risks, and constraints
• Problem-solve with practice leaders to translate the business problem into a workable Data Science solution; propose different approaches and their pros and cons
• Develop a project plan including milestones, dates, owners, and risks and contingency plans
• QA MMM input and output data sets. Translate datasets from human generated XLS to formats for MMM input. Translate MMM output to human readable outputs such as XLS and ppt.
• QA data. Answer MMM questions from the marketing, category, channel, and merchandizing teams with the help of the Neustar MMM data scientists.
• Typically, data are from a wide variety of sources, internal and external, and manipulated using SQL, spark, and Cloud big data technologies
• Assemble large, complex data sets from client and external sources that meet functional business requirements.
• Build analytics tools to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
• Perform data cleaning/hygiene, data QC, and integrate data from both client internal and external data sources on Advanced Data Science Platform. Be able to summarize and describe data and data issues
• Conduct statistical data analysis, including exploratory data analysis, data mining, and document key insights and findings toward decision making
• Train, validate, and cross-validate predictive models and machine learning algorithms using state of the art Data Science techniques and tools
• Document predictive models/machine learning results that can be incorporated into client-deliverable documentation
• Assist client to deploy models and algorithms within their own architecture

Requirements

• MS degree in Statistics, Math, Data Analytics, or a related quantitative field
• 2+ years post grad professional experience in Advanced Data Science, such as predictive modeling, statistical analysis, machine learning, text mining, geospatial analytics, time series forecasting, optimization (If you are a new grad - please apply to our All Star Positions)
• Strong Communication Skills and the ability to work under tight deadlines
• Sufficient high-level knowledge of MMM input and output formats and how MMM works
• Strong SQL, Python and Excel skills
• Proven ability to deploy machine learning models from the research environment (Jupyter Notebooks) to production via procedural or pipeline approaches
• Strong SQL, Python and Excel.
• Ability to interpret MMM output.
• Ability to work in PST
• Experience with spark and data-frames in PySpark or Scala
• Strong problem-solving skills; ability to pivot complex data to answer business questions. Proven ability to visualize data for influencing.
• Comfortable with cloud-based platforms (AWS, Azure, Google)
• Experience with Google Analytics, Adobe Analytics, Optimizely a plus