JOB OVERVIEW:

We are seeking a talented and driven Senior Data Scientist to join our team. In this role, you will play a key role in developing and maintaining machine learning models that power decision-making engines. You’ll work closely with client delivery specialists to turn data into actionable insights, streamline data-driven decision-making, and contribute to shaping Theory+Practice’s product roadmap. You will also play a technical lead role in front-line enterprise client engagements, from project scope definition to project execution and delivery. If you’re passionate about leveraging cutting-edge technologies to solve complex challenges and thrive in a collaborative, growth-oriented environment, we’d love to hear from you!

QUALIFICATIONS

• Strong Python (Numpy, Pandas, Pytorch, Tensorflow, etc.) and SQL skills
• Degree in a quantitative discipline
• 5 years of combined industry or academic experience solving analytical problems using ML approaches
• Excellent analytical skills to self-assess robustness and performance of machine learning models
• Experience and strong communication skills to explain insights and methods to both internal audiences and external clients
• Experience performing data extraction, data cleaning, exploratory data analysis and sharing results over medium to large datasets
• Experience managing data pipelines and orchestration tools
• Experience building ML models and analytical data driven solutions that have been later successfully deployed in production environments
• Experience in understanding business problems and building machine learning models and analytical solutions to these problems
• Enjoy learning new data science methods and technologies

PREFERRED QUALIFICATIONS:

• Advanced degree in a quantitative discipline (e.g. Masters or PhD in Computer Science, Engineering, Physics, Mathematics, Statistics, Economics, or related field)
• Experience with one or more of Tensorflow, Keras, Theano or Pytorch
• Familiarity with some cloud platforms like AWS, GCP, Azure and their data science stack like PySpark and other functional open source tools likeAirflow
• Familiarity with MLOps relevant to different parts like data engineering, model scaling and model deployment

• Build pragmatic, scalable and rigorous ML and AI solutions for TAP customers that enable data driven improvements for businesses such as forecasting models, optimization algorithms, recommendation engines, customer intent models, etc.
• Understand business objectives and how to achieve them through data driven ML model or analytical solutions
• Deliver effective business solutions from ideation through QA and deployment
• Work collaboratively with both internal teams (data engineers, ML engineers, project managers) and clients to define problem statements, collect data and design solutions
• Build and maintain ML models, experiments, and forecasting analytics
• Leverage Python, Spark and similar Big Data frameworks to deliver efficient analytics
• Clearly communicate the methods, impact and processes taken with clients and other stakeholders
• Guide and support junior data scientists in their projects and technical development
• Coordinate with management to identify our key strengths to allow TAP to transform our expertise and best practices into product offerings