Senior Data Scientist, Marketing Analytics

Marketing, Santa Barbara, United States

SENIOR DATA SCIENTIST, MARKETING ANALYTICS
ABOUT LOGMEIN
LogMeIn simplifies how people connect with each other and the world around them to drive meaningful interactions, deepen relationships, and create better outcomes for individuals and businesses. One of the world’s top 10 public SaaS companies, and a market leader in communication & conferencing, identity & access, and customer engagement & support solutions, LogMeIn has millions of customers spanning virtually every country across the globe. LogMeIn is headquartered in Boston with additional locations across North America, Europe, Middle East, Asia and Australia.
Our Santa Barbara campus is made up of 4 buildings and an on-site gym. The campus resembles our location, including conference room tables that look like surfboards! We offer a free bike sharing program to navigate around campus and to nearby shops and restaurants. During lunch, you will find our employees engaging in Bocce Ball, Pool, or Ping Pong. On average, we experience 70-degree days with access to the beach, mountains, and Los Angeles.
ABOUT ROLE
This is a senior-level Data Scientist position on a talented and dynamic Marketing Analytics team. This position can reside in either Santa Barbara, CA or Boston, MA. The role is most definitely data-intensive. As a Senior Data Scientist, you will offer your strategic perspective on using our data as assets. You will collaborate cross-functionally with multiple teams located in different geographies. In this Senior Data Scientist role, you will have the opportunity to explore your intellectual curiosity, while leveraging LogMeIn's state-of-the-art, Cloud-based Big Data platform, and highly diverse and rich datasets. If you are passionate about turning data into strategic assets, and leveraging Machine Learning to enhance world-class products, then LogMeIn could be the perfect fit for you and your career.
RESPONSIBILITIES
  • Work cross-functionally with Marketing stakeholders, Product Managers, Engineers, and other Data Scientists to develop and execute A/B tests to improve our products and go-to-market motions
  • Recommend A/B tests and experiments, and manage Analytics testing queue based on broader company goals and strategy
  • Sit at the cross-roads between business stakeholders, Data Scientists, and key leaders; helping to identify breakthrough ideas to be market tested
  • Establish process to ensure rigorous hypothesis testing processes
  • Ensure operational and optimal execution in a production of all data science routines and processes
  • Manage competing priorities in a dynamic and fast-paced business environment
  • Form partnerships with other Data Scientists and Analysts to evangelize the value of data science in helping the company to achieve its goals
  • Communicate broadly on the success and failure of tests, helping the business to learn optimal business practices via in-market testing
REQUIREMENTS
  • 3-5 years of experience in an analytical role, (such as customer experience, business, market, competitive or financial), and a track record of successful application of diverse analytical approaches (including but not limited to Regression Modeling, Time Series Analysis, and Decision Trees)
  • Preferred, but not required: MS or PhD in a quantitative discipline (Computer Science, Engineering, Math, Statistics, Economics or related fields)
  • Experience with A/B testing and applying derived insights to improve and fine tune processes
  • Possess an intense curiosity—a desire to deeply explore a problem, find the questions at their hearts, and distill them into a very clear set of hypotheses that can be tested
  • Able to find a story in a data set and provide a coherent narrative about a key data insight, including how this impacts both customers and the business as a whole
  • Comfortable swimming in the data (both ambiguous and unstructured data sets)
  • Basic understanding and experience with Machine Learning techniques such as Clustering, Classification, Regression, Decision Trees, Neural Nets, Support Vector Machines, Anomaly Detection, Recommender Systems, Sequential Pattern Discovery, and Text Mining
  • Good SQL development skills writing complex queries, transforming data, and mining structured and unstructured data. Experience using R, Python, SPSS, SAS, Matlab, or similar statistical packages required
  • Experience using data science to influence marketing and product strategy.
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