About us: Quantiphi is a category defining Data Science and Machine Learning Software and Services Company focused on helping organizations translate the big promise of Big Data & Machine Learning technologies into quantifiable business impact. We were founded on the belief that machine learning and artificial intelligence are transformative technologies that will create the next quantum gain in customer experience and unit economics of businesses. Quantiphi helps clients find and capture hidden value from data through a unique blend of business acumen, big-data, machine learning and intuitive information design. AthenasOwl (AO) is our “AI for Media” solution that helps content creators and broadcasters to create and curate smarter content. We launched the product in 2017 as an AI-powered suite meant for the media and entertainment industry. Clients use AthenaOwl's context adapted technology for redesigning content, taking better targeting decisions, automating hours of post-production work and monetizing massive content libraries. Please Find Attached fact sheet for your reference. For more details visit: www.quantiphi.com ; www.athenasowl.tv Job Description: -Developing high-level solution architecture related to different use-cases in the media industry -Leveraging both structured and unstructured data from external sources and our proprietary AI/ML models to build solutions and workflows that can be used to give data driven insights. -Develop sophisticated yet easy to digest interpretations and communicate insights to clients that lead to quantifiable business impact. -Building deep relationship with clients by understanding their stated but more importantly, latent needs. -Working closely with the client-side delivery managers to ensure a seamless communication and delivery cadence. Essential Skills and Qualifications: -Hands-on experience with statistical tools and techniques in Python -Great analytical skills, with expertise in analytical toolkits such as Logistic Regression, Cluster Analysis, Factor Analysis, Multivariate Regression, Statistical modelling, predictive analysis. -Advanced knowledge of supervised and unsupervised machine learning algorithms like Random Forest, Boosting, SVM, Neural Networks, Collaborative filtering etc. -Ability to think creatively and work well both as part of a team and as an individual contributor -Critical eye for the quality of data and strong desire to get it right -Strong communication skills. -Should be able to read a paper and quickly implement ideas from scratch. -A pleasantly forceful personality and charismatic communication style.
About Vedantu --------------------------- If you have ever dreamed about being in the driver’s seat of a revolution, THIS is the place for you. Vedantu is an Ed-Tech startup which is into Live Online Tutoring. Recently raised Series B funding of $11M Job Description We are looking for a Data Scientist who will support our product, sales, leadership and marketing teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product, sales and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data analysis methods, building and implementing models and using/creating appropriate algorithms. Desired Skills 1. Experience using statistical computer languages (R, Python,etc.) to manipulate data and draw insights from large data sets. 2. Process, cleanse, and verify the integrity of data used for analysis. 3. Comfortable manipulating and analyzing complex, high-volume, high-dimensionality data from varying, heterogeneous sources 4. Experience with messy real-world data -- handling missing/incomplete/inaccurate data 5. Understanding of a broad set of Algorithms and Applied Math. 6. Good at problem solving, probability and statistics and knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage) and experience with applications. 7. Knowledge of data scraping is preferable 8. Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world advantages/drawbacks. 9. Experience with big data tools (Hadoop, Hive, MapReduce) a plus.