Experience: 1- 5 Years
Job Location: WFH
No. of Position: Multiple
Qualifications: Ph.D. Must have
Work Timings: 1:30 PM IST to 10:30 PM IST
Functional Area: Data Science
NextGen Invent is currently searching for Data Scientist. This role will directly report to the VP, Data Science in Data Science Practice. The person will work on data science use-cases for the enterprise and must have deep expertise in supervised and unsupervised machine learning, modeling and algorithms with a strong focus on delivering use-cases and solutions at speed and scale to solve business problems.
Job Responsibilities:
- Leverage AI/ML modeling and algorithms to deliver on use cases
- Build modeling solutions at speed and scale to solve business problems
- Develop data science solutions that can be tested and deployed in Agile delivery model
- Implement and scale-up high-availability models and algorithms for various business and corporate functions
- Investigate and create experimental prototypes that work on specific domains and verticals
- Analyze large, complex data sets to reveal underlying patterns, and trends
- Support and enhance existing models to ensure better performance
- Set up and conduct large-scale experiments to test hypotheses and delivery of models
Skills, Knowledge, Experience:
- Must have Ph.D. in an analytical or technical field (e.g. applied mathematics, computer science)
- Strong knowledge of statistical and machine learning methods
- Hands on experience on building models at speed and scale
- Ability to work in a collaborative, transparent style with cross-functional stakeholders across the organization to lead and deliver results
- Strong skills in oral and written communication
- Ability to lead a high-functioning team and develop and train people
- Must have programming experience in SQL, Python and R
- Experience conceiving, implementing and continually improving machine learning projects
- Strong familiarity with higher level trends in artificial intelligence and open-source platforms
- Experience working with AWS, Azure, or similar cloud platform
- Familiarity with visualization techniques and software
- Healthcare experience is a plus
- Experience in Kafka, Chatbot and blockchain is a plus.
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About UpSolve
Work on cutting-edge tech stack. Build innovative solutions. Computer Vision, NLP, Video Analytics and IOT.
Job Role
- Ideate use cases to include recent tech releases.
- Discuss business plans and assist teams in aligning with dynamic KPIs.
- Design solution architecture from input to infrastructure and services used to data store.
Job Requirements
- Working knowledge about Azure Cognitive Services.
- Project Experience in building AI solutions like Chatbots, sentiment analysis, Image Classification, etc.
- Quick Learner and Problem Solver.
Job Qualifications
- Work Experience: 2 years +
- Education: Computer Science/IT Engineer
- Location: Mumbai
Job Title -Data Scientist
Job Duties
- Data Scientist responsibilities includes planning projects and building analytics models.
- You should have a strong problem-solving ability and a knack for statistical analysis.
- If you're also able to align our data products with our business goals, we'd like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Responsibilities
Own end-to-end business problems and metrics, build and implement ML solutions using cutting-edge technology.
Create scalable solutions to business problems using statistical techniques, machine learning, and NLP.
Design, experiment and evaluate highly innovative models for predictive learning
Work closely with software engineering teams to drive real-time model experiments, implementations, and new feature creations
Establish scalable, efficient, and automated processes for large-scale data analysis, model development, deployment, experimentation, and evaluation.
Research and implement novel machine learning and statistical approaches.
Requirements
2-5 years of experience in data science.
In-depth understanding of modern machine learning techniques and their mathematical underpinnings.
Demonstrated ability to build PoCs for complex, ambiguous problems and scale them up.
Strong programming skills (Python, Java)
High proficiency in at least one of the following broad areas: machine learning, statistical modelling/inference, information retrieval, data mining, NLP
Experience with SQL and NoSQL databases
Strong organizational and leadership skills
Excellent communication skills
We are looking out for a technically driven "Full-Stack Engineer" for one of our premium client
COMPANY DESCRIPTION:
Qualifications
• Bachelor's degree in computer science or related field; Master's degree is a plus
• 3+ years of relevant work experience
• Meaningful experience with at least two of the following technologies: Python, Scala, Java
• Strong proven experience on distributed processing frameworks (Spark, Hadoop, EMR) and SQL is very
much expected
• Commercial client-facing project experience is helpful, including working in close-knit teams
• Ability to work across structured, semi-structured, and unstructured data, extracting information and
identifying linkages across disparate data sets
• Confirmed ability in clearly communicating complex solutions
• Understandings on Information Security principles to ensure compliant handling and management of
client data
• Experience and interest in Cloud platforms such as: AWS, Azure, Google Platform or Databricks
• Extraordinary attention to detail
1.Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep
learning
frameworks like Tensorflow, Theano, Keras, Pytorch
2. Proficiency with modern statistical modeling (regression, boosting trees, random forests,
etc.),
machine learning (text mining, neural network, NLP, etc.), optimization (linear
optimization,
nonlinear optimization, stochastic optimization, etc.) methodologies.
3. Build complex predictive models using ML and DL techniques with production quality
code and jointly
own complex data science workflows with the Data Engineering team.
4. Familiar with modern data analytics architecture and data engineering technologies
(SQL and No-SQL databases)
5. Knowledge of REST APIs and Web Services
6. Experience with Python, R, sh/bash
Required Skills (Non-Technical):-
1. Fluent in English Communication (Spoken and verbal)
2. Should be a team player
3. Should have a learning aptitude
4. Detail-oriented, analytical and inquisitive
5. Ability to work independently and with others
6. Extremely organized with strong time-management skills
7. Problem Solving & Critical Thinking
Required Experience Level :- Senior level- 4+Years
Work Location : Pune preferred, Remote option available
Work Timing : 2:30 PM to 11:30 PM IST
with the engineering team to strategize and execute the development of data products
● Execute analytical experiments methodically to help solve various problems and make a true impact across
various domains and industries
NLP ENGINEER at KARZA TECHNOLOGIES
● Identify relevant data sources and sets to mine for client business needs, and collect large structured and
unstructured datasets and variables
● Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve
models, and clean and validate data for uniformity and accuracy
● Analyze data for trends and patterns, and Interpret data with a clear objective in mind
● Implement analytical models into production by collaborating with software developers and machine
learning engineers
● Communicate analytic solutions to stakeholders and implement improvements as needed to operational
systems
What you need to work with us:
● Good understanding of data structures, algorithms, and the first principles of mathematics.
● Proficient in Python and using packages like NLTK, Numpy, Pandas
● Should have worked on deep learning frameworks (like Tensorflow, Keras, PyTorch, etc)
● Hands-on experience in Natural Language Processing, Sequence, and RNN Based models
● Mathematical intuition of ML and DL algorithms
● Should be able to perform thorough model evaluation by creating hypotheses on the basis of statistical
analyses
● Should be comfortable in going through open-source code and reading research papers.
● Should be curious or thoughtful enough to answer the “WHYs” pertaining to the most cherished
observations, thumb rules, and ideas across the data science community.
Qualification and Experience Required:
● 1 - 4 years of relevant experience
● Bachelor/ Master’s degree in computer science / Computer Engineering / Information Technology
- Design, build web crawlers to scrape data and URLs.
- Integrate the data crawled and scraped into our databases
- Create more/better ways to crawl relevant information
- Strong knowledge of web technologies (HTML, CSS, Javascript, XPath, Regex)
- Understanding of data privacy policies (esp. GDPR) and personally identifiable information
- Develop automated and reusable routines for extracting information from various data sources
- Prepare requirement summary and re-confirm with Operation team
- Translate business requirements into specific solutions
- Ability to relay technical information to non-technical users
- Demonstrate Effective problem solving and analytical skill
- Ability to pay attention to detail, pro-active, critical thinking and accuracy is essential
- Ability to work to deadlines and give realistic estimates
Skills & Expertise
- 2+ years of web scraping experience
- Experience with two or more of the following web scraping frameworks and tools: Selenium, Scrapy, Import.io, Webhose.io, ScrapingHub, ParseHub, Phantombuster, Octoparse, Puppeter, etc.
- Basic knowledge of data engineering (database ingestion, ETL, etc.)
- Solution orientation and "can do" attitude - with a desire to tackle complex problems.
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.
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upGrad was awarded the Best Tech for Education by IAMAI for 2018-19
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upGrad was also ranked as one of the LinkedIn Top Startups 2018: The 25 most sought-
after startups in India
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upGrad was earlier selected as one of the top ten most innovative companies in India
by FastCompany.
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We were also covered by the Financial Times along with other disruptors in Ed-Tech
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upGrad is the official education partner for Government of India - Startup India
program
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Our program with IIIT B has been ranked #1 program in the country in the domain of Artificial Intelligence and Machine Learning
Role Summary
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 ourmarketing 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 careeroutcomes. 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.
Roles & Responsibilities-
- 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
Skills Required
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Experience in Text Analytics, Natural Language Processing
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Advanced degree in Data Science/Data Analytics or Math/Statistics
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Comfortable with data-visualization tools and techniques
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Knowledge of AWS and Data Warehousing
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Passion for building data-products for Production systems - a strong desire to impact
the product through data-science technique
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- Required to work individually or as part of a team on data science projects and work closely with lines of business to understand business problems and translate them into identifiable machine learning problems which can be delivered as technical solutions.
- Build quick prototypes to check feasibility and value to the business.
- Design, training, and deploying neural networks for computer vision and machine learning-related problems.
- Perform various complex activities related to statistical/machine learning.
- Coordinate with business teams to provide analytical support for developing, evaluating, implementing, monitoring, and executing models.
- Collaborate with technology teams to deploy the models to production.
Key Criteria:
- 2+ years of experience in solving complex business problems using machine learning.
- Understanding and modeling experience in supervised, unsupervised, and deep learning models; hands-on knowledge of data wrangling, data cleaning/ preparation, dimensionality reduction is required.
- Experience in Computer Vision/Image Processing/Pattern Recognition, Machine Learning, Deep Learning, or Artificial Intelligence.
- Understanding of Deep Learning Architectures like InceptionNet, VGGNet, FaceNet, YOLO, SSD, RCNN, MASK Rcnn, ResNet.
- Experience with one or more deep learning frameworks e.g., TensorFlow, PyTorch.
- Knowledge of vector algebra, statistical and probabilistic modeling is desirable.
- Proficiency in programming skills involving Python, C/C++, and Python Data Science Stack (NumPy, SciPy, Pandas, Scikit-learn, Jupyter, IPython).
- Experience working with Amazon SageMaker or Azure ML Studio for deployments is a plus.
- Experience in data visualization software such as Tableau, ELK, etc is a plus.
- Strong analytical, critical thinking, and problem-solving skills.
- B.E/ B.Tech./ M. E/ M. Tech in Computer Science, Applied Mathematics, Statistics, Data Science, or related Engineering field.
- Minimum 60% in Graduation or Post-Graduation
- Great interpersonal and communication skills
- Key Responsibilities : Use cases to support use case analysis E2E, define capabilities, understand the data and model Machine Learning Operations MLOps Azure Machine Learning, Azure Cognitive Services, Azure DevOps, Overall Azure Cloud Experience, Powershell, DSVM, AML Compute / Training Clusters Azure Infrastructure Experience, Python, Big Data Python Scripting 8 Automate ML models deployments, Manage, monitor, troubleshoot machine learning infrastructure and Setup ML Pipe lines
- Technical Experience : Proven skills experience in Azure AI ML solution design and architecture based solution using Azure Cloud capabilities AML / AKS Proven record of embedding advanced analytical models into business processes Collaborate in multi-functional teams to evaluate business activities, and then develop innovative and effective approaches to tackle teams analytics problems and communicate results bitbucket, Nodejs, PowerBI SQL, Python
- Experience in setting up MLOps framework for AI ML team
DataWeave provides Retailers and Brands with “Competitive Intelligence as a Service” that enables them to take key decisions that impact their revenue. Powered by AI, we provide easily consumable and actionable competitive intelligence by aggregating and analyzing billions of publicly available data points on the Web to help businesses develop data-driven strategies and make smarter decisions.
Data Science@DataWeave
We the Data Science team at DataWeave (called Semantics internally) build the core machine learning backend and structured domain knowledge needed to deliver insights through our data products. Our underpinnings are: innovation, business awareness, long term thinking, and pushing the envelope. We are a fast paced labs within the org applying the latest research in Computer Vision, Natural Language Processing, and Deep Learning to hard problems in different domains.
How we work?
It's hard to tell what we love more, problems or solutions! Every day, we choose to address some of the hardest data problems that there are. We are in the business of making sense of messy public data on the web. At serious scale!
What do we offer?
- Some of the most challenging research problems in NLP and Computer Vision. Huge text and image datasets that you can play with!
- Ability to see the impact of your work and the value you're adding to our customers almost immediately.
- Opportunity to work on different problems and explore a wide variety of tools to figure out what really excites you.
- A culture of openness. Fun work environment. A flat hierarchy. Organization wide visibility. Flexible working hours.
- Learning opportunities with courses and tech conferences. Mentorship from seniors in the team.
- Last but not the least, competitive salary packages and fast paced growth opportunities.
Who are we looking for?
The ideal candidate is a strong software developer or a researcher with experience building and shipping production grade data science applications at scale. Such a candidate has keen interest in liaising with the business and product teams to understand a business problem, and translate that into a data science problem. You are also expected to develop capabilities that open up new business productization opportunities.
We are looking for someone with 6+ years of relevant experience working on problems in NLP or Computer Vision with a Master's degree (PhD preferred).
Key problem areas
- Preprocessing and feature extraction noisy and unstructured data -- both text as well as images.
- Keyphrase extraction, sequence labeling, entity relationship mining from texts in different domains.
- Document clustering, attribute tagging, data normalization, classification, summarization, sentiment analysis.
- Image based clustering and classification, segmentation, object detection, extracting text from images, generative models, recommender systems.
- Ensemble approaches for all the above problems using multiple text and image based techniques.
Relevant set of skills
- Have a strong grasp of concepts in computer science, probability and statistics, linear algebra, calculus, optimization, algorithms and complexity.
- Background in one or more of information retrieval, data mining, statistical techniques, natural language processing, and computer vision.
- Excellent coding skills on multiple programming languages with experience building production grade systems. Prior experience with Python is a bonus.
- Experience building and shipping machine learning models that solve real world engineering problems. Prior experience with deep learning is a bonus.
- Experience building robust clustering and classification models on unstructured data (text, images, etc). Experience working with Retail domain data is a bonus.
- Ability to process noisy and unstructured data to enrich it and extract meaningful relationships.
- Experience working with a variety of tools and libraries for machine learning and visualization, including numpy, matplotlib, scikit-learn, Keras, PyTorch, Tensorflow.
- Use the command line like a pro. Be proficient in Git and other essential software development tools.
- Working knowledge of large-scale computational models such as MapReduce and Spark is a bonus.
- Be a self-starter—someone who thrives in fast paced environments with minimal ‘management’.
- It's a huge bonus if you have some personal projects (including open source contributions) that you work on during your spare time. Show off some of your projects you have hosted on GitHub.
Role and responsibilities
- Understand the business problems we are solving. Build data science capability that align with our product strategy.
- Conduct research. Do experiments. Quickly build throw away prototypes to solve problems pertaining to the Retail domain.
- Build robust clustering and classification models in an iterative manner that can be used in production.
- Constantly think scale, think automation. Measure everything. Optimize proactively.
- Take end to end ownership of the projects you are working on. Work with minimal supervision.
- Help scale our delivery, customer success, and data quality teams with constant algorithmic improvements and automation.
- Take initiatives to build new capabilities. Develop business awareness. Explore productization opportunities.
- Be a tech thought leader. Add passion and vibrance to the team. Push the envelope. Be a mentor to junior members of the team.
- Stay on top of latest research in deep learning, NLP, Computer Vision, and other relevant areas.