Job Brief and Requirements • We are looking for a Machine Learning/Natural Language Processing Engineer to help us improve our NLP products and create new NLP applications. • Experience in applying different NLP techniques to problems such as text classification, text summarization, question & answering, information retrieval, knowledge extraction, and conversational bots design potentially with both traditional & Deep Learning Techniques • NLP Skills/Tools: NLP, HMM, CRF, LDA, Word2Vec, Seq2Seq, spaCy, Nltk, Gensim, CoreNLP, NLU, NLG etc., • Ability to design & develop practical analytical approach keeping the context of data quality & availability, feasibility, scalability, turnaround time aspects. • Create language models from text data. These language models draw heavily from statistical, deep learning as well as rule based research in recent times around building taggers, parsers, knowledge graph based dictionaries etc. • Understanding of data creation. Develop highly scalable classifiers and tools leveraging machine learning and rules based models. • Work closely with product teams to implement algorithms that power user and developer-facing products. • Perform user research and evaluate user feedback.
Position : Head Data Science Client Name : A Fintech Start-up Job Location : Delhi Experience : 8 - 12 Yrs. (Relevant ) Qualifications : B.E. / B. Tech ( from Tier 1 Institutions) Skills Required : Candidate should have min 8 years of strong hands on Data Science, Machine Learning Algorithms experience and has worked on big data stacks. Candidate should have experience in working in any p roduct start-up/ analytics/fintech firm. Min 7+ years of expertise working on and managing analytics/data science teams with consumer-facing companies (ideally in the eCommerce and/or subscription space). Fluency in R, Python, or Julia . Experience with relational databases / SQL . Experience using Dynamo, Cassandra, Hbase , or other non-relational DB. High skill in data visualization . Proven ability to set a vision of where we will be in 2-5 years and set in place the systems-level thinking to get there. General industry knowledge of how distributed database infrastructure has been the solution to handling some of the biggest data warehouses on the planet. Solid understanding of the Data Scientist project life-cycle processes. Deep understanding how to extract data from homogeneous or heterogeneous data sources ( ETL ), and transform the data for storing it in the proper format or structure for the purposes of querying and analysis.
Want to shape the future of Energy through Data Science? We have the data and if you have got the skills to unlock the patterns behind how a little change in one input parameter can have so much impact on the optimized Energy output parameters, like energy price. The Energy Exemplar (EE) data team is looking for an experienced Applied ML Data Scientist to join our Pune office. The data team is committed to helping EE customers keep a check on how heat rate, capacity expansion and daily unit commitment are subject to variations in demand, renewables, gas price, etc. There are lots of such use cases. By continuously gathering and analysing data, and by working with organizations inside and outside EE, the data team stays agile to combat evolving challenges. Our mission is to help advice customers and systems with industry-leading proactive optimal predictions, and engage in valuable partnerships.As a dedicated Data Scientist on our Research team, you will apply data science and your machine learning expertise to enhance our intelligent systems to predict and provide proactive advice. You’ll work with the team to identify and build features, create experiments, vet ML models, and ship successful models that provide value additions for hundreds of EE customers.At EE, you’ll have access to vast amounts of energy-related data from our sources. Our data pipelines are curated and supported by engineering teams (so you won't have to do much data engineering - you get to do the fun stuff.) We also offer many company-sponsored classes and conferences that focus on data science and ML. There’s great growth opportunity for data science at EE.Responsibilities Monitor and analyse data to uncover optimization gaps Develop high-performance algorithms, machine learning models, or other methodologies to close optimization gaps. Identify performant features and models and make them universally accessible to our teams across EE. Provide technical leadership to our team by reviewing problem sets, proposing prediction models, and reviewing experiments and models. Act as a resident expert for machine learning, statistics, and experiment design. Qualifications 5+ years of professional experience in experiment design and applied machine learning predicting outcomes in large-scale, complex datasets. Proficiency in Python, Azure ML, or other statistics/ML tools. Proficiency in Deep Neural Network, python based frameworks. Proficiency in Azure DataBricks, Hive, Spark. Moderate coding skills. SQL or similar required. C# or other languages strongly preferred. Outstanding communication and collaboration skills. You can learn from and teach others. Strong drive for results. You have a proven record of shepherding experiments to create successful shipping products/services. Experience with prediction in adversarial (energy) environments highly desirable. Understanding of the model development ecosystem across platforms, including development, distribution, and best practices, highly desirable. A Masters or Ph.D degree with coursework in Statistics, Data Science, Experimentation Design, and Machine Learning highly desirable