Senior Data Scientist

PURPOSE

The Senior Data Scientist uses various analytic methods such as predictive modeling, text mining, statistical forecasting, optimization, and simulations to develop and implement advanced statistical, econometric, marketing and decision support systems to yield predictive and prescriptive insights in various areas of our business. The Senior Data Scientist assesses business needs, conducts research, and designs/develops integrated solutions to business problems.
This role will collaborate with Data Engineers to build machine learning application based on trusted data as well as provide a feedback loop of attributes derived from ML models back.

ESSENTIAL DUTIES & RESPONSIBILITIES
• Collaborate with various groups to gather, curate, and build data sets needed to successfully construct the foundation of our analytical models.
• Develop hypotheses, approaches, models, and solutions to solve problems and increase profitability and efficiency.
• Manage the execution of analytics projects based on statistics, machine learning, experimental design, and the scientific method principles to derive insights.
• Design and leverage various types of customer segmentation models to identify opportunity for growth and assess overall customer health.
• Utilize historical internal pricing data and external data to develop models to predict cost of carrier shipments to help operations improve financial outcomes
• Work with various department project teams to facilitate collaboration with cross-functional stakeholders.
• Leverage analytics and visualization tools to design and present information to drive fact-based decision making.
• Develop subject matter expertise on internal and external sources of information.
• Stay up to date with the industry trend to gain knowledge of the latest hardware and software, emerging technologies, and analytic techniques to ensure we are utilizing state-of-the-art tools

REQUIRED KNOWLEDGE/SKILLS/ABILITIES
• Expertise with statistical languages such as R and/or Python
• Strong understanding of statistics and probability: distributions, experimental design, variance analysis, A/B testing, probability theory, stochastic systems, and Bayesian inference
• Expertise with various statistical modeling algorithms such as: regression, clustering, ARIMA, decision trees, Time Series, and simulation
• Knowledge of multiple business functional areas. Excellent executive presence and ability to communicate at all-levels of the organization.
• Excellent problem solving, logical thinking, negotiating, and influencing skills.

QUALIFICATIONS:
• Databricks and Spark, pyspark
• SQL
• Tableau/Power BI
• Python programming and expertise with ML libraries like XGBoost, NumPy and Keras
• Accessing data via APIs

PHYSICAL DEMANDS & WORK ENVIRONMENT
Work Environment: Job is typically performed in a general office environment.

Physical Requirements
NP Not Present
O Occasional (Up to 25% of time)
F Frequent (26%-74% of time)
C Constant (75% or more of time)