Responsible for end-to-end data science cycles, encompassing designing, training, implementing, evaluating, and monitoring machine learning models.
Design and implement highly scalable tools and algorithms based on state-of-the-art Machine Learning and Deep Learning methodologies.
Work across the ML stack, from researching models, working with large datasets, training, and tuning existing models to creating new models, deploying them at scale.
Analyze results, and present findings to stakeholders across tech and business domains.
Develop and implement advanced predictive models to optimize customer experiences and other business outcomes.
Collaborate with cross-functional teams to ensure proper deployment and integration of ML models for new releases.
Requirements
Bachelor's degree in data science, statistics, and computer science is a MUST.
Google Cloud - Professional Machine Learning Engineer Certificate
Google AgentSpace implementation experience
3-4+ Years of experience in data science or machine learning.
Must have strong experience in at least one of the following areas:
Vision models
NLP models (Experience in Arabic NLP is a huge plus)
Proficient in python, TensorFlow, keras and pytorch.
Good experience in: SQL and non-relational databases.
Data analytics reports generation.
ML model development deployment.
Benefits
Professional development opportunities
Flexible work arrangements
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.