Junior Data Scientist

**Are you the next Junior Data Scientist at Theory+Practice?**

Theory+Practice is a rapidly growing data science company focused on bringing cutting edge AI/ML solutions to unlock value for companies with large data sets.

Our Fortune 500 clients leverage our Intelligent Intervention Frameworks to make strategic decisions about the right moments and actions to improve customer journeys and maximize key business metrics.

We attract independent thinkers who share a desire for excellence within an open culture. If you have passion for leveraging state of the art analytics to solve complex problems, we invite you to join our team

**Description**

The Junior 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, Hadoop, 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**
- Degree in a STEM field (e.g. Computer Science, Engineering, Physics, Mathematics, Statistics, Economics, or related field)
- Strong working knowledge of probability and statistics
- 2 years of industry or academic experience solving analytical problems
- Experience performing data extraction, data cleaning, exploratory data analysis and sharing results over medium to large datasets
- Strong Python (NumPy, SciPy, Pandas, Scikit-learn etc.) and SQL skills
- Strong data analytics skills (e.g. matplotlib, seaborn, plotly)
- Good communication skills to explain insights and methods
- Excellent analytical skills to self-assess robustness and performance of machine learning models
- Enjoy learning new data science methods and technologies
- Preferred: 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
- Preferred: Experience with data analytics tools like Tableau, Looker, Power BI
- Preferred: Experience with MLOps relevant to different parts like data engineering, model scaling and model deployment
- Preferred: Experience with one or more of Tensorflow, Keras, Theano or Pytorch
- Preferred: Experience in understanding business problems and building machine learning models and analytical solutions to these problems