Senior Manager Data Scientist

Our client is looking for a Senior Manager Data Scientist for a 6-month contract and will be working remotely.

Join the team at this advanced technology communications provider that's been around for nearly a century and be part of a mission to improve people's opportunities by connecting them to the power of the digital world.

Contract Duration: 6 Months
Required Skills & Experience

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Marketing Analytics, or a related quantitative field.
• 7-10 years of Python experience.
• 7-10 years of SQL experience.
• 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.
• Strong collaboration and teamwork.
• Able to translate business requirements into technical solutions.

Desired Skills & Experience

• Master's degree in Data Science, Statistics, Computer Science, Analytics, or a related field.
• Telecommunications industry experience.
• Data engineering experience.
• AI/GenAI knowledge.
• 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.

What You Will Be Doing Daily 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.

Data Engineering

• 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.

Applicants must be currently authorized to work in the US on a full-time basis now and in the future.