Main responsibilities:

Apply data science expertise in machine learning, deep learning, statistics, text-mining/NLP, forecasting and optimization to multiple analytics projects
Deve models, algorithms, simulations, and experiments by writing highly optimized code and using state-of-the art machine learning technologies
Work on full-spectrum of activities, from conducting ML experiments to delivering production-ready models
Use data analysis, visualization, storytelling, and data technologies to scope, define and deliver AI-based data products
Work closely with product owners, developers, engineers, and MLOps to deliver AI/ML solutions
Adhere to and promote to best practices and standards for data science process (including documentation) and code developments
Remains up to date with industry practices and emerging technologies such as generative AI and test creative ways of offering AI solutions to enhance existing solutions
Mentor and coach junior data scientists and interns
About you
Key Functional Requirements and Qualifications:

Hands-on AI/ML modeling experience of complex datasets combined with strong understanding of theoretical foundations of AI/ML.
Expertise within most of the following areas: supervised learning, unsupervised learning, deep learning, reinforcement learning, federated learning, time series forecasting, Bayesian statistics, optimization
Experience developing deployable code and deploying models in product-focused development under an agile environment
Comfortable working in cloud and high-performance computing environments (e.g. AWS, GCP, Databricks, Apache Spark)
Experience in production-ready software development
Experience in leading the data science projects and working closely with junior data scientists and data analysts
Excellent written and verbal communication, business analysis, data visualization and data storytelling skills
Nice to have experience in life sciences and healthcare and experience in a complex global organization
A demonstrated ability to work and collaborate in a team environment
Ability to work in a fast-paced, constantly evolving environment and to manage multiple priorities
Fluent in English (Other languages a plus)
Key Technical Requirements and Qualifications:

PhD in computer science, mathematics, physics, statistics or a related quantitative discipline with strong coding skills, OR Master’s Degree in relevant domain with 6+ years of analytical experience
Expertise with core data science languages (such as Python, R, Scala), and experience working with different database systems (such as SQL, NoSQL)
Should have experience of AI/ML development (CI/CD, Orchestration)
Experience working in cloud-based environment such as AWS or GCP or Azure and using cloud-technologies for building AI-solutions
Knowledge of Tableau, Power BI, Plotly or similar
Experience with various enterprise-level Application Programming Interfaces (APIs)
Nice to have experience in using some data science tools such as datarobot, dataiku, Alteryx