Job Location: Bangalore/Bengaluru
Responsibilities:
- You shall lead, manage and hire a team of talented data scientists and MLOps engineers.
- Collaborating with your team, you will craft a thoughtful, long-term technical
strategy that anticipates future needs while being pragmatic about whats
needed today.
- You will have practical exposure of being a technical contributor and mentor for
your team. While most of your focus will be on people management, youre not
afraid to roll up your sleeves and do actual technical work when appropriate.
- You will set the right metrics and goals for your team, by focusing on the outcome and not on the inputs.
- You will check and confirm the accuracy and effectiveness of the work performed and the methods used by engineering team, including code and architecture reviews.
- You shall create detailed engineering plans, processes, and procedures for engineering staff to use and abide by.
- Youll define clear requirements for the infrastructure needs to make your team as productive as possible.
- You will work with other engineering managers and functional leads to set
direction and ambitious goals for your team, Engineering, and Sense as a
whole.
Qualifications
- Masters or PhD in the field of Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent.
- 8+ years of experience working in the tech or consumer industry.
- 5+ years of experience managing Machine Learning, Research, and/or Applied ML teams.
- Evidence of doing or directing data science work with high positive impact on business outcomes.
- Experience hiring and leading experienced data scientists as well as a successful record of developing junior members to a successful career track.
- Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, that have been successfully integrated in production systems or informed policy decisions.
- Demonstrable expertise in research design methodologies (e.g., experiments, quasi-experiments, surveys, sampling methods, etc).
Languages and technologies we use (and teach):
- Python for development
- Keras/Tensorflow/Pytorch for training ML models
- SQL for storing and processing analytics data from the bot
- AWS for training and serving ML models is a plus
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