Candidate should have e-commerce experience and must be an IIT or NIT GRADUATE.
About Us upGrad is an online education platform building the careers of tomorrow by offering the most industry-relevant programs in an immersive learning experience. Our mission is to create a new digital-first learning experience to deliver tangible career impact to individuals at scale. upGrad currently offers programs in Data Science, Machine Learning, Product Management, Digital Marketing, and Entrepreneurship etc. upGrad is looking for people passionate about management and education to help design learning programs for working professionals to stay sharp and stay relevant and help build the careers of tomorrow. upGrad was awarded the Best Tech for Education by IAMAI for 2018-19 upGrad was also ranked as one of the LinkedIn Top Startups 2018: The 25 most sought-after startups in India upGrad was earlier selected as one of the top ten most innovative companies in India by FastCompany. We were also covered by the Financial Times along with other disruptors in Ed-Tech upGrad is the official education partner for Government of India - Startup India program too Our program with IIIT B has been ranked #1 program in the country in the domain of Artificial Intelligence and Machine Learning Job Description We're looking for a hands-on technical leader to head the Data Science and Data Engineering vertical within the Technology team who can work alongside Business stakeholders & Product managers to drive the creation of data-driven products/platforms. Responsibilities: Ownership of end-to-end initiatives across all products and services in upGrad in the data domain - data engineering, data science, and product analytics Lead, mentor and guide our team of Data Analysts, Data-Engineers and Data Scientists Establishment and execution of the tech data roadmap balancing short term and long term needs to ensure that the architecture can scale and evolve Data Engineering would entail envisioning and extending our Redshift data-warehouse Architecting robust data-ingestion pipelines from internal and external sources Domain schema creation and democratizing data for all stakeholders Monitoring and Administration of all data services and tech that goes with it Mentoring and guiding our data-engineers to execute on these initiatives Data Science would entail ideating, development and delivery of data-science backed products and services across entire upGrad domain - Learn, Career, Sales and Marketing Understanding the business domain and ideating/brainstorming potential data-science solutions Collaborating with Product & business stakeholders on feasibility, impact, execution, delivery as well as adoption Hands-on architecting, reviewing and mentoring the data-science team to execute on these projects/initiatives both on data and tech side and deploy them into the Production environment Data Analytics would entail envisioning and supporting all product analytics initiatives. Ease of access of the right data-points and visualizations to enable teams to make strong data-backed decisions at all aspects in upGrad Guiding/Mentoring our data analysts on approach and data sources available for delivering on the analytics required Understanding all the nitty-gritty of the Product and end-to-end user delivery to able to deliver holistic analytics Collaborating with product and business stakeholders to make sure their data needs are fulfilled as per the need and feasibility Owning the administration of the various data-analytics tools and services. Overall would be a data evangelist who is constantly pushing the team to collect, organize, share and utilize data in meaningful ways to better the product and it’s services. At it’s core who is serious about data integrity, data security as well as ethical sourcing/utilization of data Qualifications: A suitable candidate in this position will be a strategic/innovative thinker who is proactive and self-drives requires minimal supervision and is able to build a strong data-focused team. A Tech Data expert, goto person for all things data, software and technology. 6+ years of experience in leading and building strong data-powered products and services Master’s or higher education in the field of Stats, Data, Computer Science preferred Hands-on experience in building data-warehouse, ETL pipelines from scratch and supporting those in Production Environments. Hands-on experience in building and deploying machine learning/natural language processing based data-products Strong drive to understand the domain and sharp analytical thinker to ideate on how data-driven products/services can help drive the business Strong programming skills in Python and SQL Strong understanding of relational and non-relational databases Strong understanding of the various technologies/tools/libraries upcoming and available in this area and can drive the adoption of those as per the business needs and future growth Ability to handle multiple simultaneous projects, prioritize and meet tight impact based deadlines; alongside being organized and calm when while dealing with a lot of uncertainties and unknowns Excellent interpersonal and communication skills
What will you do? ------------------------ Solve problems in speech and NLP domain using advanced Deep learning and Machine Learning techniques. Few examples of the problems are - * Limited resource Speaker Diarization on mono-channel recordings in noisy environment. * Speech Enhancement to improve accuracy of downstream speech analytics tasks. * Automated Speech Recognition for accent heavy audio with a noisy background. * Speech analytic tasks, which include: emotions, empathy, keyword extraction. * Text analytic tasks, which include: topic modeling, entity and intent extraction, opinion mining, text classification, and sentiment detection on multilingual data. A typical day at work ----------------------------- You will work closely with the product team to own a business problem. You will then model the business problem into a Machine Learning problem. Next you will do literature review to identify approaches to solve the problem. Test these approaches, identify the best approach, add your own insights to improve the performance and ship that to production! What should you know? --------------------------------- * Solid understanding of Classical Machine Learning and Deep Learning concepts and algorithms. * Experience with literature review either in academia or industry. * Proficiency in at least one programming language such as Python, C, C++, Java, etc. * Proficiency in Machine Learning tools such as TensorFlow, Keras, Caffe, Torch/PyTorch or Theano. * Advanced degree in Computer Science, Electrical Engineering, Machine Learning, Mathematics, Statistics, Physics, or Computational Linguistics Why DeepAffects? -------------------------- * You’ll learn insanely fast here. * Esops and competitive compensation. * Opportunity and encouragement for publishing research at top conferences, paid trips to attend workshop and conferences where you have published. * Independent work, flexible timings and sense of ownership of your work. * Mentorship from distinguished researchers and professors.
Does the current state of media frustrate you? Do you want to change the way we consume news? Are you a kickass machine learning practitioner and aspiring entrepreneur, who has opinions on world affairs as well? If so, continue reading! We at UnFound are developing a product which simplifies complex and cluttered news into simple themes, removes bias by showing all (& often unheard of) perspectives, and produce crisp summaries- all with minimal human intervention! We are looking for passionate and experienced machine learning ENGINEER/INTERN, *preferably* with experience in NLP. We want someone who can take initiatives. If you need to be micro-managed, this is NOT the role for you. 1. Demonstrable background in machine learning, especially NLP, information retrieval, etc. 2. Hands on with popular data science frameworks- Python, Jupyter, TensorFlow, PyTorch. 3. Implementation ready background in deep learning techniques like word embeddings, CNN, RNN/LSTM, etc. 4. Experience with productionizing machine learning solutions, especially ML powered mobile/ web-apps/ BOTs. 5. Hands on experience on AWS, and other cloud platforms. GPU experience is strongly preferred. 6. Thorough understanding of back-end concepts, and databases (SQL, Postgres, NoSQL, etc.) 7. Good Kaggle (or similar) scores, MOOC (Udacity, Coursera, fast.ai, etc.) preferred.