Senior Data Scientist 5351

Tier4 Group; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Tier4 Group in the United States seeks a Senior Data Scientist for Advanced Analytics to build and deploy machine learning models that optimize customer acquisition, retention, pricing, and marketing effectiveness.

You will own the end-to-end ML lifecycle, collaborate with Marketing, Product, Finance and Technology, and translate complex data into actionable insights that drive measurable business impact in a highly competitive telecommunications environment.

Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Marketing Analytics, or a related field.
• 7+ years of experience in data science, machine learning, or advanced analytics.
• Strong programming skills in Python and SQL.
• Experience with BigQuery, BigQuery ML, and cloud-based analytical environments.
• Hands-on experience with machine learning libraries such as scikit-learn, XGBoost, LightGBM, and pandas.
• Strong understanding of predictive modeling, statistical analysis, experimentation, feature engineering, model validation, and machine learning best practices.
• Experience building machine learning models and automated analytical pipelines.
• Excellent communication skills with the ability to translate complex analytical findings into business recommendations.

Responsibilities

• Develop and deploy scalable predictive and ML solutions for marketing, pricing, and customer analytics.
• Own end-to-end ML lifecycle: design, feature engineering, deployment, monitoring, and retraining.
• Apply advanced statistics, experimentation, and analytics to business challenges.
• Develop ML solutions using BigQuery ML and Python libraries.
• Communicate insights via visualizations and executive presentations.
• Research and implement emerging AI/ML technologies to enhance capabilities.
• Develop robust SQL transformations and data pipelines in BigQuery.
• Build reusable datasets and automated training pipelines.
• Ensure data quality through validation, testing, monitoring, and governance.
• Partner with Data Engineering and IT to support production ML.

Skills

Python programming

SQL

BigQuery

BigQuery ML

Cloud analytics

Machine learning libraries

Model lifecycle management

Communication with stakeholders

Education

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Marketing Analytics, or a related field

Master's degree (preferred)

Tools

Power BI

Job description

The Senior Data Scientist, Advanced Analytics, develops machine learning models and advanced analytical solutions that optimize customer acquisition, retention, pricing, and marketing effectiveness. This role leverages predictive modeling, experimentation, and cloud-based machine learning technologies to solve complex business problems and deliver measurable business impact. Working closely with Marketing, Product, Finance, and Technology, the Senior Data Scientist transforms complex data into actionable insights that improve business performance in a highly competitive telecommunications environment.

Key Responsibilities

Advanced Analytics & Data Science

• Develop and deploy scalable predictive and machine learning solutions that improve customer acquisition, retention, pricing strategies, and marketing performance.
• Own the end-to-end machine learning lifecycle, including model design, feature engineering, development, validation, deployment, monitoring, optimization, and continuous improvement to deliver accurate, reliable, and production-ready solutions.
• Apply advanced statistical techniques, machine learning, predictive analytics, and experimentation to solve complex business challenges, identify growth opportunities, and optimize business performance.
• Develop machine learning solutions using BigQuery ML and Python libraries, including scikit-learn, XGBoost, LightGBM, and pandas.
• Communicate analytical insights and actionable business recommendations through compelling visualizations, dashboards, and executive-level presentations.
• Research, evaluate, and implement emerging AI and machine learning technologies to continuously enhance analytical capabilities and business outcomes.
• Develop robust SQL transformations and scalable data pipelines in BigQuery.
• Build reusable datasets, feature stores, and automated model training and scoring pipelines.
• Implement model monitoring, performance tracking, and automated retraining processes to ensure long-term model accuracy and reliability.
• Ensure data quality through validation, testing, monitoring, and governance best practices.
• Partner with Data Engineering and IT to build and maintain scalable analytics infrastructure supporting production machine learning solutions.

Business Impact

• Improve customer acquisition and retention through predictive analytics.
• Optimize pricing strategies through price elasticity modeling and customer response analytics.
• Optimize marketing campaigns and sales channel performance using data-driven insights.
• Increase operational efficiency through scalable automation and reusable analytical assets.
• Deliver accurate, validated insights that influence strategic business decisions.
• Build sustainable machine learning solutions that create long-term competitive advantage.

Qualifications Required

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Marketing Analytics, or a related quantitative field.
• 7+ years of experience in data science, machine learning, or advanced analytics.
• Strong programming skills in Python and SQL.
• Experience with BigQuery, BigQuery ML, and cloud-based analytical environments.
• Hands-on experience with machine learning libraries such as scikit-learn, XGBoost, LightGBM, and pandas.
• Strong understanding of predictive modeling, statistical analysis, experimentation, feature engineering, model validation, and machine learning best practices.
• Experience building machine learning models and automated analytical pipelines.
• Excellent communication skills with the ability to translate complex analytical findings into business recommendations.

Preferred

• Masters degree in Data Science, Statistics, Computer Science, Analytics, or a related field.
• Telecommunications industry experience.
• Experience with Power BI or similar visualization platforms.
• Experience with speech analytics platforms (NICE, Verint, CallMiner), natural language processing (NLP), and Generative AI/LLM applications.