Data Scientist

Innoplexus offers Data as a Service and

Continuous Analytics as a Service products, leveraging Artificial Intelligence and advanced analytics to help reduce the time to market, significantly.

Our products leverage proprietary algorithms and patent pending technologies to help global Life sciences & Financial services organizations with access to relevant data, real time intelligence & intuitive insights, across the life cycle of the products.

We automate the collection, curation, aggregation, analysis & visualization, of billions of data points from thousands of data sources, using domain-specific language processing, ontologies, computer vision, machine learning, network analysis and more.

Key Responsibilities:

• Develop solutions for realworld noisy data, large-scale problems
• Develop highly scalable deep learning algorithms to improve our products
• Develop state-of-the-art machine learning and neural network methodologies to improve our intelligence platform
• Use machine learning & deep learning techniques to create new, scalable solutions for business problems
• Develop NLP & computer vision-based tools and technologies for acquiring, parsing, interpreting and visualizing unstructured data
• Analyse and extract relevant information from large amounts of data to help in automating the solutions and optimizing key processes
• Help team in building large scale continuous/online learning systems
• Help team to build experimentation to production pipeline
• Stay up-to-date with the latest research and technology and communicate your knowledge throughout the enterprise
• Create IP for Innoplexus through patents and publications

Required Experience:

• Strong track record in AI/ML publications in renowned scientific journals or conferences
• Experience in any of the following: Computer Vision, Image Processing, Speech Recognition, Natural Language Understanding, Machine Learning, Deep Learning, HCI, Text Mining, Computational Genomics, Bioinformatics, other Machine Learning and Artificial Intelligence related areas
• Experience in Graph algorithms and Graph Embeddings(node2vec, graph2vec)
• Strong in Python programming Knowledge of commonly used machine learning tools: pytorch, scikit-learn, gensim, pandas
• Knowledge and hands-on experience in Computational Genomics and Bioinformatics is good to have

Required qualification:

• MS in Computer Science, Statistics, Applied Maths or related domain
• Degree in Computer Science, related Machine Learning field or equivalent practical