Data Scientist (Computer Vision)

Key Skills

Azure, Computer Vision (CV), Data science techniques, Deep Learning, Effective communication skills, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, SPARK Programming, Statistics, Teamwork, TensorFlow

Job Description

At Kaizen, our aim is to make data-driven decisions in order to automate our servicers while also focusing on offering a tailored customer experience. Our machine learning team is dedicated towards this mission by building a variety of models, from binary classification tasks up to recommendation systems. We focus on transforming business needs into production applications and we cover a wide range of business sectors, utilizing different data types and handling a broad project diversity. 

Our teams comprise of three different roles, data scientists, machine learning engineer and data engineers so that they include the full skillset to deliver projects to production.

The Role

We are currently looking for experienced data scientists with experience in computer vision to join our teams. The role should combine strong knowledge of machine learning algorithms, analytical skills, experimental design, etc. to support the model development process.

Responsibilities:

• Translate business requirements to machine learning problems;
• Perform EDA and feature engineering;
• Run comparative experiments for model training;
• Implement best practices on model selection, parameter tuning, etc.

Requirements

Must have:

• A background in Computer Science, Statistics, Math or related field;
• Strong knowledge of machine learning algorithms, statistical concepts and deep learning for vision;
• Proven track record of implementing and scaling vision models in a production environment;
• Strong coding skills in python and the relevant machine learning/data science libraries;
• 3+ years of hands-on experience with deep learning frameworks, such as TensorFlow or Pytorch;
• Solid software background in OOP;
• Strong skills in teamwork, communication, and analytical thinking;
• Fluency in English, both oral and written.

Nice to have:

• Experience with cloud computing (e.g. Azure);
• Experience with distributed computing (e.g. Spark);
• Knowledge of other machine learning areas (e.g. NLP);
• Experience in recommendation systems.