Data Scientist/Senior Data Scientist – ML/DL

As a Data Scientist, your responsibilities will include:

• Developing algorithms and constructing systems to uncover hidden trends and insights from user-generated content such as resumes, job descriptions, and profile information sourced from diverse channels and in various formats including numeric, structured, unstructured texts, and images.
• Identifying potential new business challenges that could benefit from machine learning solutions.
• Conceptualizing, devising metrics, and executing strategies to address these challenges, while obtaining stakeholder buy-in.
• Recognizing opportunities for data-driven machine learning models to enhance user experience through personalized recommendations and predictive analytics.
• Creating intelligent systems to capture and model extensive behavioral data to enhance content understanding with behavioral insights.
• Selecting appropriate machine learning tools for a range of tasks in natural language processing (NLP), deep learning, semantic search, and learning to rank (LTR) to develop highly accurate and scalable recommendation systems and information retrieval solutions.
• Designing solutions for scalability and real-time performance on large datasets, leveraging big data technologies to optimize infrastructure and enhance performance.
• Actively engaging in external forums and discussions, publishing research papers, staying updated on the latest advancements in the field, and building both external and internal networks.

Required Skills:

• Strong foundational understanding and research experience in machine learning, deep learning, NLP, information retrieval, and artificial intelligence.
• Applied knowledge of machine learning techniques for solving real-world business problems, encompassing a broad spectrum of algorithms for classification, regression, discriminative, generative, supervised, unsupervised, semi-supervised learning, as well as linear and non-linear dimensionality reduction, feature extraction, selection, and learning.
• Industry experience in applying machine learning solutions to large-scale datasets to develop intelligent systems.
• Excellent problem-solving skills with a research-oriented mindset.
• Proficiency in managing, creating pipelines, and processing big data.