Key Responsibilities:
Identify valuable data sources and automate collection processes.
Undertake preprocessing of structured and unstructured data.
Analyze large amounts of information to discover trends and patterns.
Build predictive models and machine-learning algorithms.
Combine models through ensemble modeling.
Present information using data visualization techniques.
Propose solutions and strategies to business challenges.
Collaborate with engineering and product development teams.
Communicate your findings to the appropriate teams through visualizations.
Collaborate and communicate findings to diverse stakeholders.
Provide solutions but not limited to: Image recognition, natural language processing, Sentiment Analysis, Concept Extraction, Recommender Systems, Clustering, Customer Segmentation, Propensity Modeling, Churn Modeling, Lifetime Value Estimation, Forecasting, Modeling Response to Incentives, Marketing Mix Optimization, Price Optimization.
Follow/maintain an agile methodology for delivering on project milestones.
Excellent oral, presentation, and written communication skills.
Preferred Qualifications:
Bachelors in Math, Computer Science, Information Systems, Machine Learning, Statistics, Econometrics, Applied Mathematics, Operations Research or related technical degree.
Minimum of 3+ years of experience in a related position, as a data scientist building predictive analytics or NLP or CV solutions for various types of business problems.
Working knowledge of statistical techniques, NLP, machine learning algorithms and deep learning frameworks like TensorFlow, Pytorch, PySpark.
Programming background and expertise in building models using at least one of the following languages: Python, R, C, C++, Spark, Scala.
Good knowledge in the implementation of deep learning models for image classification, Document classification models, object detection, logo detection.
Self-motivated and driven to deliver agreed results on-time.