Principal Data Scientist

Principal Data Scientist

Requirements

• Bachelor’s Degree in Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Required)
• 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 hands on experience developing deep learning models (Required)
• 7-10 years of Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data. (Required)
• 7-10 years of Experience with data scripting languages (e.g., SQL, Python, R) and Extended experience working with relational database using SQL (Required)
• 4-7 years of Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations (Required)
• 4-7 years of Experience with statistical methods and advanced modeling techniques. For example- SVM, Random Forest, graph models, Bayesian inference, NLP, Computer Vision, neural networks. (Required)
• 4-7 years of Experience with big data architecture and pipeline, Hadoop, Hive, Spark, Kafka, etc. (Required)
• 4-7 years of Experience in data visualization (Required)
• 2-4 years Management consulting, investment banking, or corporate strategy (Required)
• Mathematics: Calculus, linear algebra, statistics, and probability (Required)
• Programming: Mastery of Python and SQL (Required)
• Machine Learning: Apply machine learning techniques including supervised and unsupervised learning; collaborative filtering; and artificial neural networks (Required)
• Deep Learning: Research, design, implement, evaluate, and optimize novel algorithms/models in Deep Learning space (Required)
• Communication: Exemplary communication skills, ability to work with cross functional teams

Responsibilities

• Extract, prepare, and model large, complex data sets using a combination of skills, including machine learning theory, mathematics, statistics, and programming.
• Identify critical and emerging technologies that will support and extend our consumer data, data integration, and quantitative analytic capabilities.
• Lead the implementation, assessment and standardization of advanced analytics and modeling toolkits for our data science team.
• Partner with data engineering teams to shape data management strategies, architecture, governance, pipelines, and infrastructure enabling effective modeling environments for data science teams
• 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.
• Also responsible for other Duties/Projects as assigned by business management as needed.

Preferred Qualifications

• Master’s/Advanced Degree Quantitative Discipline (math, statistics, economics, computer science, physics, engineering) (Preferred)
• Experience in the telecom industry preferred.