Aftersales Data Scientist Job Franklin area,Tennessee USA,IT/Tech

Work Authorization:

This position is open to U.S. Citizens and Green Card holders only. Unfortunately, visa sponsorship is not available for this role, and we are unable to consider candidates requiring current or future sponsorship.

We are seeking an experienced Aftersales Data Scientist to join a high-performing analytics team. In this role, you will leverage advanced analytics, machine learning, and AI to develop predictive models that drive business growth, optimize marketing investments, improve sales performance, and support strategic decision-making.

Key Responsibilities:

Design, develop, and deploy predictive, prescriptive, and AI-driven analytics models.
Perform end-to-end model development, including data extraction, cleansing, feature engineering, model training, validation, and deployment.
Build and maintain advanced dashboards, reports, and business intelligence solutions using SQL, Python, Snowflake, AWS, Power BI, and Informatica Prep.
Develop scalable data pipelines and ETL processes to support analytics and business initiatives.
Identify and integrate relevant internal and external data sources to uncover actionable business insights.
Collaborate with business stakeholders, analytics teams, and IT to gather requirements and deliver data-driven solutions.
Design experiments and statistical analyses to validate business hypotheses and measure solution effectiveness.
Monitor and improve the performance of predictive models and decision-support systems.
Analyze large, complex datasets to identify opportunities related to marketing effectiveness, inventory optimization, customer retention, and sales performance.
Present findings and recommendations to technical and business stakeholders while serving as a trusted analytics advisor.

Required Qualifications:

Bachelor's degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
6+ years of experience in data science, machine learning, predictive analytics, and statistical modeling.
Strong programming skills in Python and advanced SQL.
Experience with Snowflake, AWS, Power BI, and ETL/data pipeline development.
Strong understanding of machine learning algorithms, forecasting, optimization, multivariate testing, and statistical analysis.
Experience working with large structured and unstructured datasets.
Ability to translate complex business problems into scalable analytical solutions.
Excellent communication and presentation skills with the ability to explain technical concepts to non-technical audiences.

Preferred Qualifications:

Master's degree in a related field.
Experience in the automotive industry or other consumer-facing industries.
Experience with dynamic pricing models.
Knowledge of dealer operations, service retention, customer lifecycle analytics, or marketing optimization is a plus.

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