Applied Scientist Machine Learning
Applied Scientist Machine Learning
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Job Description
Your Mission
You will be part of a joint team of machine learning engineers data scientists data analysts and product managers building and evolving ML models realtime systems reports and performing deep analysis of pricing retention and offer strategies.
Working with advanced predictive models MLOps best practices and scalable software systems you will implement and evolve intelligent solutions to align Teya with the success of our customers.
In this role youll be:
Helping Teya to use data to drive business decisions by implementing and continuously improving through experimentation advanced machine learning models.
Working on projects including but not limited to customer lifetime value churn propensity forecasting risk costtoserve and costtoacquire modelling
Building predictive models to a production level adopting best practices for coding deployment monitoring and experimentation.
Qualifications :
Your Story
Background in a quantitative field (Computer Science Mathematics Machine Learning AI Statistics Economics or equivalent)
5 years of professional working experience
Someone who thrives in the incremental delivery of high quality production systems
Proficiency in Java Python SQL Jupyter Notebook
Experience with Machine Learning and statistical inference.
Understanding of ETL processes and data pipelines and ability to work closely with Machine Learning Engineers for product implementation
Ability to communicate model objectives and performance to business stakeholders
Strong analytical and problemsolving skills
Ability to think creatively and insightfully about business problems
Nice to have:
Proficiency with Snowflake
Proficiency with Amazon SageMaker
Proficiency with Docker and Kubernetes
Additional Information :
The Perks
We trust you so we offer flexible working hours as long it suits both you and your team;
Health Insurance;
Meal Allowance;
25 days of Annual leave Bank holidays);
Public Transportation Card;
Frequent team events & activities in the office and outside;
Office snacks every day;
Friendly comfortable and informal office environment.
Remote Work :
No
Employment Type :
Fulltime
Employment Type
Full-time
