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Marketing Lead Data Scientist
  • Python
  • Spark
  • SQL
  • Machine Learning
  • Big Data
  • Database
  • ETL
  • Modeling
  • Hadoop
  • A/B Testing
  • NoSQL
  • Bayesian
  • Azure
UPS
Atlanta, GA
118 days ago

The Lead Data Scientist uses various analytic methods such as predictive modeling, text mining, machine learning, statistical forecasting, optimization, and simulations to develop and implement advanced statistical, econometric, marketing and decision support systems to yield predictive and prescriptive insights in various areas of UPS business. The Lead Data Scientist assesses business needs, conducts research, and designs/develops integrated solutions to business problems. Successful candidate will work with a team that is responsible for researching and implementing advanced analytics models utilizing a diverse set of techniques.

This individual will perform some data wrangling, ETL, and data exploration tasks, leveraging large volumes of structured and unstructured data. He/she will manage projects across the lifecycle, working with cross functional teams consisting of data scientists, data engineers, application developers, business analysts and marketing stakeholders. He/she will provide advanced analytic thought leadership for project teams. This individual will also manage and develop other data scientists

Responsibilities and Duties

  • Collaborate with various groups to gather, curate, and build data sets needed to successfully construct the foundation of our Analytical Models
  • Develop hypotheses, approaches, models, and solutions to solve problems and increase profitability and efficiency
  • Manage the execution of analytics projects based on statistics, machine learning, experimental design, and the scientific method principles to derive insights
  • Design and leverage various types of customer segmentation models to identify opportunity for growth and assess overall customer health
  • Work with various department project teams and facilitates collaboration with cross-functional stakeholders
  • Integrate marketing performance and impact within the sales to drive coordination between Marketing and Operational initiatives
  • Leverage analytics and visualization tools to design and present information to drive fact-based decision making
  • Develop subject matter expertise on internal and external sources of information
  • Stay up to date with the industry trend to gain knowledge of latest hardware and software, emerging technologies, and analytic techniques to ensure UPS is utilizing state-of-the-art tools
  • Manages other data scientists

Knowledge and Skills

  • Master's Degree with 5+ years' experience or a Ph.D. with 2+ years of advanced analytics experience (Degree in Operational Research, Mathematics, Engineering, Statistics, Econometrics or related field) - Preferred
  • Expertise with statistical languages such as R and/or Python
  • Strong understanding of statistics and probability: distributions, experimental design, variance analysis, A/B testing, probability theory, stochastic systems, and Bayesian inference
  • Expertise with various statistical modeling algorithms such as: regression, clustering, ARIMA, decision trees, Time Series, and simulation
  • Expertise in machine learning algorithms and experience using the following ML techniques: Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Clustering and Neural Networks
  • Working experience with database systems (e.g. SQL, NoSQL, Teradata, MongoDB, Postgres, etc.)
  • Experience with Big Data technologies like Hadoop, Spark, Hive, NoSQL, etc., and Cloud technologies (Google Cloud, Azure, etc.) - Preferred
  • Advanced skills to work with large, complex, and disparate data (accessing, connecting, and analyzing) - Preferred

UPS is an equal opportunity employer. UPS does not discriminate on the basis of race/color/religion/sex/national origin/veteran/disability/age/sexual orientation/gender identity or any other characteristic protected by law

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