Principal Data Scientist

About the Role

Key Responsibilities

• Extract, prepare, and model large, complex data sets using skills including machine learning theory, mathematics, statistics, and programming.
• Identify critical and emerging technologies to support and extend consumer data, data integration, and quantitative analytic capabilities.
• Lead the implementation, assessment, and standardization of advanced analytics and modeling toolkits for the data science team.
• Partner with data engineering teams to shape data management strategies, architecture, governance, pipelines, and infrastructure to enable effective modeling environments.
• Provide senior-level guidance to the data science and measurement science teams on approach and methodologies.
• Communicate important information and insights to business leaders using verbal, written, and data visualization skills.
• Perform other duties or projects as assigned by business management as needed.

Requirements

• Bachelor's Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering).
• 7-10 years of industry experience in predictive modeling, data science, and analysis in an ML engineer or data scientist role building and deploying ML models or developing deep learning models.
• 7-10 years of experience articulating and translating business questions and using statistical techniques to analyze data.
• 7-10 years of experience with data scripting languages (e.g., SQL, Python, R) and working with relational databases using SQL.
• 4-7 years of experience in technical communication, including giving data-driven presentations to diverse audiences.
• 4-7 years of experience with statistical methods and advanced modeling techniques such as SVM, Random Forest, Bayesian inference, NLP, Computer Vision, neural networks.
• 4-7 years of experience with big data architecture and pipelines including Hadoop, Hive, Spark, Kafka.
• 4-7 years of experience in data visualization.
• 2-4 years of experience in management consulting, investment banking, or corporate strategy.
• Mathematics skills including calculus, linear algebra, statistics, and probability.
• Proficiency in Python and SQL.
• Ability to apply machine learning techniques including supervised and unsupervised learning, collaborative filtering, and neural networks.
• Research, design, implement, evaluate, and optimize algorithms/models in Deep Learning.
• Exemplary communication skills and ability to work with cross-functional teams.
• At least 18 years of age and legally authorized to work in the United States.

Nice to Have

• Experience in the telecom industry.

Qualifications

• Bachelor's Degree in a relevant quantitative discipline.
• 7-10 years of industry experience in data science, predictive modeling, and ML model deployment.
• Experience with data scripting languages and relational databases.
• Experience in technical communication and data visualization.
• Experience with advanced modeling techniques and big data architectures.

Benefits & Perks

• Competitive base salary and compensation package.
• Annual stock grant, employee stock purchase plan, 401(k).
• Access to free, year-round money coaching.
• Medical, dental, and vision insurance.
• Flexible spending account, paid time off, and up to 12 paid holidays.
• Paid parental and family leave, family building benefits, back-up care, childcare subsidy, tuition assistance, college coaching.
• Disability, voluntary AD&D, accident, life, and long-term care insurance.
• Mobile service and home internet discounts, pet insurance, commuter and transit programs.