The big picture
Cardlytics makes marketing more relevant and measurable through our Purchase Intelligence™ platform. With purchase data from financial institutions (FIs), Cardlytics has a secure view into where and when consumers are spending their money. By applying advanced analytics to this massive aggregation of purchase data, we make it actionable, helping marketers/ advertisers identify, reach and influence likely buyers at scale, and measure the true sales impact of their marketing spend.
What you will accomplish
- The Data Scientist will be a subject-matter expert on various analytical tools such statistical programming languages, graph databases, and machine-learning algorithms and provide this expertise throughout Cardlytics as needed
- The Data Scientist will create, test, and deploy models in a development environment that will impact new lines of business for the company
- Learn new practices, design iterative learning and development cycles, and deliver prototypes to other groups for deployment into production and operations
- Build full scale data science models for production
Skills and experiences that will make you successful
- Knowledge of advanced statistical modeling, testing, data mining, and data science techniques
- Advanced in modeling frameworks including Scikit-learn, PyTorch, and TensorFlow
- Highly proficient in Python and SQL
- Proficiency in Linux working in shell
- Experience with H2O, Data Robot or other automated AI tools are a plus
- Advanced Excel and PowerPoint skills required
- Experience with Tableau and other data visualization is preferred
- Strong scientific approach to problem-solving
- Excellent organizational, analytical and problem-solving skills
- Ability to communicate complex results in a simple and concise manner at all levels within the organization
- Ability to excel in a fast-paced, startup environment
- 2+ years of proven success in a position of similar responsibilities or equivalent research time in an academic environment
- Proficient in the use of Python or other leading statistical software/languages
- Proficient in scripting processes in a Linux environment
- Proficient with Data Sciences frameworks such as SkLearn, Tensorflow, and Pytorch.
- Ability with Java a plus.
- Experience with Python test automation frameworks a plus
OURSTORY In 2008, Scott Grimes and Lynne Laube were bankers who understood the power of purchase data – if only it could be harnessed. With deep insight into the complex regulations that financial institutions face, they designed a bank- and privacy-friendly solution that would also serve as the foundation for marketing technology and analytics. In doing so, they linked two major industries: banking and marketing. And Cardlytics was born. Today, Cardlytics operates with a clear goal in mind: to make marketing more relevant and measurable with Purchase Intelligence.