How often have you read job descriptions and gone ‘I have read this before’ or ‘the real job description will come out during the interviews, so why bother reading this’. In other instances when job descriptions are actually well-written, ie not just copied and pasted from somewhere and try doing justice to what you’d be doing at the job, 2-4 months of a typical interview cycle make those descriptions obsolete by the time you actually start at the job. Also not unsurprising then: just like you ignore or skim through job descriptions, most recruiters do the same with your resumes – look for specific keywords and leave all the assessment for during the interview itself. Even worse: the human recruiter in some cases is being replaced by an algorithm to automate screening. You, therefore, will try to put as many keywords in your resume to ensure you get that interview call. Nobody is being ingenuine in this process but the very process is fundamentally broken. And that is exactly what we want to solve: create an effective ‘matching of work to the worker’ that is an accurate and real-time reflection of both ends, thus increasing the actual engagement with the work itself. Responsibilities In this role, you’ll build and implement novel Machine Learning and Deep Learning systems on our platform as well as help build the infrastructure to train and deploy them. Specifically, you will: - Design and implement the infrastructure required to train models at scale. - Work with the data team’s infrastructure to build real-time and offline feature databases. - Work with the data team to create the infrastructure to build and maintain the datasets from which models are created - Build the model serving systems with which we can deploy our models to production - As we grow, scale the ML system to be able to support more use cases and ML model types. Requirements - 1+ years of experience building production-ready ML models and systems. - 3+ years of building distributed systems and/or scalable backend systems and the ability to maintain such systems in production. - Strong software engineering fundamentals - understanding of data structures and algorithms, O-notation, ability to maintain a test suite and write clear maintainable code. - Familiarity with the majority of the following tools: Tensorflow, Numpy, Scipy, SparkML, pandas, scikit-learn. - Demonstrated leadership and self-direction and willingness to both teach others and learn new techniques. - Experience with big data processing and storage systems: Hadoop, Spark, Hbase, Cassandra etc. - Strong programming skills in Python. Intermediate to Advanced knowledge of SQL and ability to wrangle data from many disparate data sources - Technologies we use: MySQL, Python, AWS, Snowflake, R, and Looker, among many others.
About UpGrad : 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 Analytics, Product Management, Digital Marketing, and Entrepreneurship, and was rated as one of the top 10 most innovative companies in India for 2017 - https://www.fastcompany.com/most-innovative-companies/2017/sectors/india . We plan to launch 6 more programs in technology and management education. UpGrad is co-founded by 3 IITD alumni, and the 4th co-founder is serial entrepreneur Ronnie Screwvala. UpGrad has a committed capital of 100Cr and in the first year of operations, has built the largest revenue generating online program in India (PG Diploma in Data Analytics) and the largest enrolment online program in India (Startup India learning program). 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. Position : Senior Data Scientist Position Type : Full Time Location : Mumbai Job Description: Are you excited by the challenge and the opportunity of applying data-science and data-analytics techniques to the fast developing education technology domain? Do you look forward to, the sense of ownership and achievement that comes with innovating and creating data products from scratch and pushing it live into Production systems? Do you want to work with a team of highly motivated members who are on a mission to empower individuals through education? If this is you, come join us and become a part of the UpGrad technology team. At UpGrad the technology team enables all the facets of the business - whether it’s bringing efficiency to our marketing and sales initiatives, to enhancing our student learning experience, to empowering our content, delivery and student success teams, to aiding our student’s for their desired career outcomes. We play the part of bringing together data & tech to solve these business problems and opportunities at hand. We are looking for an highly skilled, experienced and passionate data-scientist who can come on-board and help create the next generation of data-powered education tech product. The ideal candidate would be someone who has worked in a Data Science role before wherein he/she is comfortable working with unknowns, evaluating the data and the feasibility of applying scientific techniques to business problems and products, and have a track record of developing and deploying data-science models into live applications. Someone with a strong math, stats, data-science background, comfortable handling data (structured+unstructured) as well as strong engineering know-how to implement/support such data products in Production environment. Ours is a highly iterative and fast-paced environment, hence being flexible, communicating well and attention-to-detail are very important too. The ideal candidate should be passionate about the customer impact and comfortable working with multiple stakeholders across the company. Basic Qualifications: 3+ years of experience in analytics, data science, machine learning or comparable role Bachelor's degree in Computer Science, Data Science/Data Analytics, Math/Statistics or related discipline Experience in building and deploying Machine Learning models in Production systems Strong analytical skills: ability to make sense out of a variety of data and its relation/applicability to the business problem or opportunity at hand Strong programming skills: comfortable with Python - pandas, numpy, scipy, matplotlib; Databases - SQL and noSQL Strong communication skills: ability to both formulate/understand the business problem at hand as well as ability to discuss with non data-science background stakeholders Comfortable dealing with ambiguity and competing objectives Preferred Qualifications: Experience in Text Analytics, Natural Language Processing Advanced degree in Data Science/Data Analytics or Math/Statistics Comfortable with data-visualization tools and techniques Knowledge of AWS and Data Warehousing Passion for building data-products for Production systems - a strong desire to impact the product through data-science techniques
We're looking for Senior NLP Engineer (2+ years experience) for our company - Spotmentor Technologies. Right now our Technology team has 5 members and this role is for early team member and carries significant ESOPs with it. We need someone who can lead the NLP function with both vision and hands-on work and is excited to use this area to develop B2B products for enterprise productivity.RESPONSIBILITIES----------------------- • Collaborate with cross-functional team members to develop software libraries, tools, and methodologies as critical components of our computation platforms. • Use independent judgment to take existing code, understand its function, and change/enhance as needed. • Work as a team leader rather than a member. • Capable of adding valuable inputs to existing algorithms by reading NLP research papers.REQUIREMENTS-------------------- • Proficient in Python with sound knowledge in the data science libraries namely Numpy, Pandas, NLTK / spaCy etc. • Prior experience in building a fully functional NLP based Machine Learning Model with good results (NER/Classification/Topic Modeling). • Expert data scientist with professionalism in text classification, feature engineering, using embeddings, pos etc. • Knowledge of writing database queries (SQL/NoSQL). • Some background in information retrieval systems is a big plus.