Senior Data Scientist - Sales Analytics and Techno

Key Skills

Analytical and Problem solving, Data science techniques, Database, Large data sets, Machine learning techniques, PaaS, Python Programming, PyTorch, R Programming, SAS, SPSS Statistics, SQL, TensorFlow

Job Description

• Develop advanced models, tools, and templates to drive the planning, forecasting and budgeting processes.
• Research, design, develop, implement, and support decision-science models.
• Evaluate accuracy of data, reporting, and forecasting outputs and perform adjustment to maximize commercial impact.
• Understand, forecast and optimize the core drivers of revenue
• Responsible for complete, accurate and timely reports such as monthly enterprise forecast reports to senior leadership team, ad-hoc and automated reporting to provide insight into revenue results and performance tracking for internal customers.
• Design and develop advanced analytical data mining, forecasting, estimation, simulation, and/or optimization models.
• Provide science calibration support for decision-science models. Perform data collection, data cleaning, data validation, and reporting tasks for analytical systems and applications.
• Lead the analysis and validation of statistical, forecasting, and optimization models.
• Communicate analytical results to business partners and clients.
• Provide ad-hoc reporting, advanced analysis and support to Sales and Product stakeholders and senior leadership.
• Serve as technical consultant in the fields of operations research, data science, decision analytics, and applied mathematics.
• Identify and apply best practices in field of advanced analytics.

Requirements

Minimum Qualifications:

• Option 1- Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 3 years' experience in an analytics related field.

OR

• Option 2- Master’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology, or related field and 1 years' experience in an analytics related field.

OR

• Option 3 - 5 years' experience in an analytics or related field.

Preferred Qualifications:

• Bachelor's degree in computer science, Statistics, Operations Research, Econometrics, Applied Mathematics, Machine Learning, Decision Science, Industrial Engineering, or related field.
• 5+ years of experience in applying advanced analytics to support business decisions, yielding measured outcomes improvement.
• Expert‐level fluency in applying advance multivariate statistical analysis (logistic & linear regression, decision tree, cluster analysis, ANOVA, Time-Series, ARIMA) to categorize, classify, and detect relationships in large datasets.
• Proficiency in extracting and cleansing large datasets from different data sources.
• Mastery of analytical tools, including spreadsheet modeling, relational databases/SQL, and statistical analysis tools (e.g. R, SAS, SPSS), Pytorch, Tensorflow
• Demonstrated proficiency in programming with knowledge of SQL, R, SAS, Python, or other similar languages.
• Ability to understand complex business requirements and define key performance metrics to measure benefits and communicate complex quantitative analysis in a clear, precise, and actionable manner.
• Strong, demonstrated problem solving skills involving both business problems and people interactions.