Responsibility
- Lead projects in Data Science. Collaborate with Engineering and Client Success teams to understand requirements, prioritize projects, and ensure seamless integration of data science models into our product.
- Designing, implementing, monitoring and maintaining Data Science systems that power the Aera platform.
- Research and build new statistical/machine-learning models.
- Performing Data Analysis for a variety of business problems across different domains. Clearly presenting the results to stakeholders and management.
- Ensuring quick support and resolution of issues raised in Data Science skills raised by client teams.
- Testing of new features on the Data Science platform.
- Mentor and coach team members, fostering a culture of continuous learning and innovation within the data science team.
Nice to have
- Master’s Degree in Computer Science, Mathematics, Statistics, or a related quantitative field with a focus on Machine Learning or Deep Learning.
- 7+ years of professional experience as a Machine Learning Engineer/Data Scientist; in a product development setting.
- First and foremost, you are someone who is obsessed about solving customer problems using Data Science. You understand the importance of solving customer problems in a timely manner.
- Experience in Full-Cycle Data Science projects. Hands-on experience with software development, including translating ML models into scalable production servicesGood intuitive understanding of machine learning algorithms and practical experience building models with incremental/iterative approach.
- Experience in implementing time-series and machine learning algorithms using APIs/libraries from sci-kit-learn, H2O & TensorFlow.
- Experience in working with large data sets and pipelines, distributed systems for machine learning using frameworks such as Dask and Ray.
- Should be very strong in SQL and Python. Should know how to write high-quality and high-performance code in SQL and Python. Knowledge of R (specifically with regards to time-series libraries) is a strong plus.
- Nice to have: Experience in leading teams.
0 applies
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