Do you enjoy design research and analytic frameworks? How would you like to use your creative and analytical skills alongside business leadership in your everyday work? If this sounds appealing, we would love to hire someone with your skills and abilities!

As a PhD Data Scientist, you'll be using Big Data and advanced analytics to direct the engagement of our business leaders

• Collaborating actively across functional partners and senior management to accomplish various project objectives.
• Executing research and analytics, including data source identification, processing, model/algorithm development.
• Turning insights into actionable recommendations which will drive business value creation.

We need someone who is technically capable as a Data Scientist. You will get into the details of the data, demonstrating artificial intelligence and analytic tools (R, Python, Scala, Spark, TensorFlow, Hadoop, KNIME, etc.) to unlock business building insights in our mountains of data. You must be adept at demonstrating technologies for solving ad hoc business problems, innovating on potential future solutions, and working with technology partners to translate your innovations into robust, scaled, analytic solutions.

Qualifications

Required

• Pursuing or has graduated with a PhD in a quantitative field (Operation Research, Computer Science, Engineering, Applied Math, Statistics, Physics, Analytics, etc.) or have equivalent work experience.
• Proven leadership in applying and scaling Analytic techniques to deliver impactful insights from data (in academics or in industry.
• Strong written and verbal communication skills to influence others to take action.
• Able to balance multiple priorities.
• Good social skills, self-motivated, dynamic with a can-do mentality.
• Strong enthusiasm and curiosity about the intersection of business and technology

PREFERRED

• Experience in disrupting current business practices in CPG or related industries to help crafting a new go-to-market models.
• Experience with Analytical Tools/Applications including:
• Unix/Linux
• Big Data Ecosystem: Hadoop, Spark, MapReduce, SQL, HIV
• Scientific Computing: R, Python, C++, Java, Scala, etc.
• High-Performance Parallel and Distributing Computing
• Deep Learning frameworks: Keras, Tensorflow
• Data Visualization
• Data Management Systems
• Business Intelligence tools: such as KNIME, Tableau