Data Scientist (Mid)-Data & Analytics-IT-CS-US
Infotree Global Solutions
- United States
- United States
About
The primary responsibilities of this role, Data Scientist - customer analytics are to:
Develop & Deliver: • Deliver best-in-class analytics solutions for the customer-centric commercial operations of the company. Topics include but are not limited to customer analytics, segmentation analysis, predictive cross-sell, churn prediction, and agronomic recommendation. Results will drive business decisions and significant revenue. • Develop practical, interpretable, and automated solutions for these business problems through expertise in feature engineering, statistical analysis, predictive modeling (classification and regression), simulation, and optimization methodology by working in a highly interactive, team-oriented environment. • Write model documentation to detail problem formulation, modeling approach, validation, data requirements, and implementation steps. • Support stakeholder requests for model development, implementation, and feature improvements, and be able to communicate results to a broad range of audiences in a clear, interpretable manner.
Collaborate & Communicate: • Work closely with data science teams and business partners to break down complex business problems, and gather requirements to build feasible solutions that are impactful, accurate, and validated. • Collaborate with system integration and data warehouse engineers on data extraction and data cleaning (ETL). • Be creative, resourceful, detail-oriented, able to take initiative, and exercise critical thinking when it comes to problem-solving. • Be a proactive member of a global data science team to adopt and advocate for coding best practices and documentation.
Required Qualifications: • Bachelor's degree with at least 4 + of experience, Master's degree with 2+ years of experience, or a Ph.D. in one of the following areas: Data Science, Economics, Electrical/Industrial Engineering, Applied Mathematics, Statistics, Computer Science, or another related quantitative discipline. • Experience conducting statistical inferences, time-series analysis, statistical simulation, analysis, and building machine learning models using disparate sources of data. • Advanced programming skills in R or Python or both employing object-oriented programming, good programming practices, use of IDEs, adherence to code style and good documentation for machine-learning tasks, and working knowledge of version-control tools (such as git and git workflows including CLI). • Excellent work ethic, and a strong desire to learn new skills for technical and professional growth.
Preferred Qualifications: • Experience in related fields where data science techniques are used, including economics/econometrics, math, computer science, operations research, physics, and engineering. • Experience working with SQL, GCP, and AWS, on the command line, containerization /deployment (Docker), and interactive visualization tools such as R-shiny, flask, fast API, and/or Dash is a plus. • Experience with Agile development practices and Data Science Lifecycle best practices.
Languages
- English
Notice for Users
This job comes from a TieTalent partner platform. Click "Apply Now" to submit your application directly on their site.