AVP - Business Development & Recruitment at Career Experts
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Data Scientist - Internet/IT/Analytics Firm (2-5 yrs)
Job Description Summary :
The ideal candidate is a team player who will be responsible for working with company's data in various business areas. Specific responsibilities Conceptualize, design and deliver high-quality solutions and insightful analysis, Work and collaborate with other teams to deliver and create value for clients, Fast learner, ability to learn and pick up a new language/ tool/ platform quickly.
We are looking for a talented and passionate Data Scientists to join our Data Science Team, which is responsible for building and deliver AI/ML based solutions around a host of domains and business problems, with some of them being: Customer Segmentation & Targeting, Propensity Modelling, Churn Modelling, Lifetime Value Estimation, Recommender Systems,
Modelling Response to Incentives.
Essential Responsibilities :
- Problem-solving, ability to break the problem into small problems and think of relevant techniques which can be explored & used to cater to those
- Fast learner, ability to learn and pick up a new language/ tool/ platform quickly.
- Good communication skills and strong ability to work effectively in a team environment
Educational Qualification/Experience :
- Bachelor's/Master's degree in Engineering/Computer Science/Mathematics/Operational research/Statistics.
- At least 2 years of experience of having designed and implemented advanced AI/ML in different projects.
- Expert level proficiency in Python or R, Python being preferred.
- Expert level proficiency in RDBMS and SQL
- Experience of working on a project end-to-end: problem scoping, data gathering, EDA, modelling, insights, and visualizations
- Advanced knowledge of machine learning, probability theory, statistics, Deep-Learning architectures and algorithms.
- Should be able to use regression, classification, Bayesian methods, neural networks, tree-based learners, SVM, RF, XGBOOST, time series modelling, dimensionality reduction, clustering, NLP etc. on a regular basis.
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