Data Scientist Lead - Employee Platforms
Data Scientist Lead - Employee Platforms
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Job Description
Revolutionize the future of Employee Platforms with cuttingedge AI and Data Science! Join a dynamic team dedicated to creating innovative cloudcentric solutions that transform client experiences and drive industryleading advancements.
As a Data Scientist Lead in Employee Platforms you will collaborate with a team of innovators to develop AI/ML solutions. Your work will directly impact our ability to provide exceptional service to clients by delivering cuttingedge technology solutions. Each day you will engage in endtoend software development from design to deployment in a fastpaced cloudnative environment that values continuous learning and innovation. Your contributions will help keep our Employee Compute services at the forefront of the industry.
Job responsibilities
- Develop and deploy machine learning models and generative AI capabilities.
- Design code test and debug applications.
- Collaborate with crossfunctional teams to achieve common goals.
- Keep stakeholders informed on development progress and benefits.
- Manage project lifecycle and software development deliverables.
- Solve complex problems and handle ambiguity with strong analytical skills.
Required qualifications capabilities and skills
- Bachelors or Masters in Computer Science or related field
- Strong programming skills in python and knowledge of software engineering best practices
- Strong knowledge of basic data science libraries in Python (NumPy pandas scikitlearn pyspark)
- Strong knowledge of the main deeplearning frameworks such as PyTorch TensorFlow Keras
- Experience with Linux and shell scripting and experience with LaTeX
- Solid understanding of traditional data science techniques and experience with data engineer pipelines for big data
- Solid knowledge of RNNs and LSTMs models
Preferred qualifications capabilities and skills
- Experience with cloudnative development and deployment Knowledge of AWS cloud services is a plus.
- Familiarity with project lifecycle and version control practices.
- Experience with machine learning algorithms on graphs.
- Strong ability to collaborate in a diverse global team environment.
Employment Type
Full-Time
