The Senior Data Scientist will design, develop and implement valuable business solutions for the organization by preparing and cleaning data, designing and coding decision support systems and measuring the performance of the recommended decisions. These applications will identify business trends and opportunities using advanced decision science. The candidate will interpret data from multiple sources using a variety of statistical and complex data mining techniques in order to provide guidance to the business and contribute to the value we deliver to its customers.

ACCOUNTABILITIES

Design and develop decision support systems from the ground up that will improve business effectiveness and performance.

Analyze and interpret results from multiple sources using a variety of techniques, ranging from simple data clustering to more advanced classification problem using supervised learning techniques with cross validation.

Prepare big data, implements data models and develops database to support the business solutions.

Coordinate and communicating effectively across diverse functional teams (business leaders and technical teams) the applied logic as well as the data and the information used.

Prepare high-level and detail-level project plans and ensure that each project objective is being completed within the agreed upon deadlines.

EDUCATION & EXPERIENCE

Masters Degree in applied statistics, computer science, or related field of study required. Minimum of three years work experience in a big data environment.

SKILLS & CERTIFICATIONS

• Hands-on technical and functional experience in building predictive modeling, decision support systems and datamining analysis in a big data environment
• Experience in software engineering:
• Deep knowledge of Python programming, Python libraries such as Pandas, NumPy, Scipy, PyBrain, etc.
  Solid experienced with SQL and writing procedures
  Knowledge of R programming and prototyping
• Knowledge of Operations Research and decision sciences with the following:
• Forecasting (Consumer Choice Modeling (Logit regression), time series, ANOVA, etc.)
  Segmentation models (CART, random forest, decision tree, etc.)
  Machine learning and deep learning (reinforcement learning)
• Pricing analytics and revenue management (dynamic pricing, revenue optimization, price testing, etc.)
• Experience in problem solving and delivering workable solutions
• Team player who enjoys working in a collaborative, agile environment
• Good communication skills with the ability to explain the significance of data in a way that can be easily understood by others
• Strong attention to detail, proficient organizational skills
• Very high initiative and drive for organizational success