Senior Data Scientist

We are looking for a Data Scientist to design and develop Machine Learning (ML) models in different domains to find patterns from wide-variety types and large amounts of datasets. You will use mainly Deep Learning techniques (and other ML techniques) to solve different problems in Recommendation Engines, Chatbots, Natural Language Processing (NLP) and other domains. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research. Your goal will be to help our company analyze trends to make better decisions.

Responsibilities

Analyze raw data : assessing quality, cleansing, preprocessing, structuring for downstream processing. Conduct research and development activities, data exploration and discovery using Data Science and Machine Learning (ML) practices. Develop, apply, test and implement Data Science and ML models for a wide variety of datasets gathered from different data sources such as Online market places, e-commerce platforms, social media, and web sources. Design and develop accurate and scalable ML models in different domains and applications, which include, but not limited to, Recommendation engines, Chatbots, NLP, text mining, text-based feature selection / representation, optimization and predictive modeling. Utilize a variety of tools and approaches to solve complex business objectives, from Recommendation Engines, Chatbots, Natural Language Processing (NLP), Machine Learning / Deep Learning, Image Processing, Speech Processing, Rule-Based Learning and Knowledge Graphs. Design new service offerings and solutions in E-Commerce and different fields. Keep up to date with latest trends and technologies in the data science and ML fields. Work closely with Data Engineers in data related requests, and Data Quality Assurance Officers in data integrity issues. Work closely with Business Analysts and product development teams to understand and implement their requirements. Collaborate with big data and software developers to translate ideas, models and prototypes into full-fledged solutions. Work closely with cross-functional teams to identify challenges and problems and suggest potential AI solutions.

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