Tags: jd TheoryPlusPractice DataScientist
Senior Data Scientist (Mat. Leave Cover) Theory+Practice · Vancouver, BC 5 days ago · 62 applicants
11-50 employees
Senior Data Scientist (Mat. Leave Cover) Theory+Practice Vancouver, BC Hybrid
Description
A Senior Data Scientist will join our growing group of AI specialists and software engineers at Theory+Practice working closely with client business specialists to systematize data driven insights and decision making. If you have a passion for leveraging new technologies and methods to solve complex problems, and love to be in an environment that fosters growth while being part of a great team we invite you to consider joining our team!
Responsibilities
- Build pragmatic, scalable and rigorous ML and AI solutions for TAP customers that enable data driven improvements for businesses such as recommendation engines, opportunity scoring frameworks, customer intent models, etc.
- Understanding business objectives and how to achieve them through data driven solutions - ML models or analytical solutions
- Deliver effective business solutions from ideation to 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
- Lead and support junior data scientists in their projects and technical development
- Coordinate with the management to identify key strength of TAP to transform our expertise and best practices into product offerings
Qualifications
- Strong Python (NumPy?, SciPy?, Pandas, Scikit-learn 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
- Strong SQL skills
- Strong communication skills to explain insights and methods
- Experience performing data extraction, data cleaning, exploratory data analysis and sharing results over medium to large datasets
- Experience building ML models and analytical data driven solutions that have been later successfully deployed in production
- 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 Dataproc, PySpark?, Cassandra, Redshift, BigQuery?, EKS/GKE and other functional open source tools like DVC, Airflow
- Familiarity with data analytics tools like Tableau, Looker, Power BI Familiarity with MLOps relevant to different parts like data engineering, model scaling and model deployment-