Responsibilities :
- Experience in Computer Vision is MUST.
- Build innovative analytics solutions and partner with product and business teams to improve existing solutions.
- Lead and counsel the data science team in choosing the right approach for problem-solving.
- Collaborate with Data Scientists and Data engineers to enable deployment of solutions.
- Architecting DS/AI/ML solutions for easy integration with product.
- Identify new opportunities to build data science solutions.
- Experience deploying DS/ML/AI solutions
- Ability to discover patterns in data and deliver impactful insights.
- Ability to convert high level business problems into analytics problems.
- Experience Managing data science teams and Experience working with business users / clients
- Design, build, test and deploy ML models at scale
- Experience with modern machine learning techniques including Ensemble Methods,
- Recommender Systems, NLP and Deep learning
- Hypothesis Testing and Design of experiments to analyse and monitor results
- Engineer features to improve decision algorithms
- Partner with data/ML engineers and vendor partners for input data pipes development and ML models automation
Skills and Experience :
- ML algorithms ( Supervised / Unsupervised Learning, Clustering, Time Series Forecasting, recommender systems, Deep learning)
- Languages and packages - Python, Spark, PySpark, SparkML, MLlib, Tensorflow, NLP Packages like NLTK
- Knowledge in cloud platform - Microsoft Azure ADF, Azure kafka, Azure Databricks, Databricks MLflow
- Experience building scalable / highly available distribute systems in production
- Hands-on experience in Data Science with exposure to online recommender systems, NLP, traditional ML
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