Lead Decision Scientist
- Atlanta, GA, USA
Moxie is a modern marketing solutions agency that expertly leverages the value of data, content and technology to help our clients grow. We push the boundaries of what's possible to outperform the competition in the areas of strategy, creative, social marketing, media, analytics and technology development. Founded in 2000, Moxie has 300+ talented employees in Atlanta, Los Angeles, New York and Pittsburgh. Owned by global media giant Zenith — part of the Publicis Groupe — Moxie is able to quickly leverage cross-company areas of enterprise, talent, experience, resources and tools. Moxie's client roster includes Verizon Wireless, Verizon FiOS, Delta, Porsche, American Cancer Society, Ocean Spray, Wells Fargo, The Coca-Cola Company, 20th Century Fox, Chick-fil-A, Nike, Ainsworth Pet Nutrition and Cisco Systems.
Leading the use of modeling, algorithms, and clustering to transform marketing, the Sr Decision Scientist must be passionate about mathematics and innovation to help our clients leverage data for real time decisions for our clients
Does that sound like you?
Major Tasks, Responsibilities and Key Accountabilities
- Client/Account facing responsibilities representing data science solutions
- Delivers the next best innovation in the use of data science for the agency and our clients
- Responsible for driving the structure and utilization of data science methodologies
Nature, Scope & Job Requirements
- Reports to Director, Decision Science
- Bachelor’s degree
Years of Relevant Experience
- 3-5 years of data science experience
Preferred Qualifications, Knowledge, Skills, Abilities & Competencies
- Master’s degree from top tier college/university in Computer Science, Statistics, Economics, Physics, Engineering, Mathematics, or other closely related field.
- Strong understanding and application of statistical methods and skills
- Statistical emphasis on data mining techniques, Bayesian Networks Inference, CHAID, CART, association rule, linear and non-linear regression, hierarchical mixed models/multi-level modeling, and ability to answer questions about underlying algorithms and processes.
- Experience with both Bayesian and frequentist methodologies.
- Mastery of statistical software, scripting languages, and packages (e.g. Python (Scikit-learn ), R, Matlab, etc.).
- Knowledge of or experience working with database systems (e.g. SQL, NoSQL, MongoDB, Postgres, etc.)
- Experience working with big data distributed programming languages, and ecosystems (e.g. S3, EC2, Hadoop/MapReduce, Pig, Hive, Spark, SAP HANA, ect.)
- Expertise in machine learning algorithms and experience using the following ML techniques: Logistic Regression, Decision Trees, Random Forests, Gradient Boosting, SVMs, Time Series, KMeans, Clustering, NMF).
- Preferred experience with at least one of the following NLP/NLU, Graph Theory, Neural Networks (RNNs/CNNs).
- Experience building and deploying predictive models.
- Excellent team-oriented interpersonal skills and demonstrated leadership.
- Proven track record delivering successful data science projects
- Demonstrated leadership by building Data Science teams and fostering growth.
All your information will be kept confidential according to EEO guidelines.