Data Scientist

This role is primarily responsible for building AIML models and cognitive applications

Principal Accountabilities :

1. Good in communication and converting business requirements to functional requirements

2. Develop data-driven insights and machine learning models to identify and extract facts from sales, supply chain and operational data

3. Sound Knowledge and experience in statistical and data mining techniques: Regression, Random Forest, Boosting Trees, Time Series Forecasting, etc.

5. Experience in SOTA Deep Learning techniques to solve NLP problems.

6. End-to-end data collection, model development and testing, and integration into production environments.

7. Build and prototype analysis pipelines iteratively to provide insights at scale.

8. Experience in querying different data sources

9. Partner with developers and business teams for the business-oriented decisions

10. Looking for someone who dares to move on even when the path is not clear and be creative to overcome challenges in the data.

Graas uses predictive AI to turbo-charge growth for eCommerce businesses. We are “Growth-as-a-Service”. Graas is a technology solution provider using predictive AI to turbo-charge growth for eCommerce businesses. Graas integrates traditional data silos and applies a machine-learning AI engine, acting as an in-house data scientist to predict trends and give real-time insights and actionable recommendations for brands. The platform can also turn insights into action by seamlessly executing these recommendations across marketplace store fronts, brand.coms, social and conversational commerce, performance marketing, inventory management, warehousing, and last mile logistics - all of which impacts a brand’s bottom line, driving profitable growth.

 

Location – Pune

Job Responsibilities

• Work closely with data scientists and data analysts to build models and continuous data monitoring workflows.
• Implement algorithms / models within companies recommendation engine framework.
• Own the MLOps life-cycle; build and own ML model life-cycle management process encompassing coding to building robust model monitoring workflows.
• Consult with product and business teams to build prototypes and then deploy holistic machine learning solutions.
• Recommend and implement architecture to deploy machine learning pipelines and CI/CD processes at scale

Skills Needed

• Minimum 3 years of experience as Machine Learning Engineer
• Knowledge of machine learning and statistics
• Strong experience working in the areas of time series analysis, reinforcement learning, NLP, optimization and heuristics based implementation to solve real-world problems
• Experienced in architecting solutions with Continuous Integration and Continuous Delivery in mind
• Strong knowledge of coding in Python and libraries such as Pandas, Numpy, Scikit-Learn, PyTorch, etc.
• Experience handling Big Data leveraging technologies like Snowflake, Spark. Ability to work in a big data ecosystem - expert in SQL and ability to work in distributed databases.
• Able to refactor data science code and has collaborated with data scientists in developing ML solutions.
• Experience playing the role of full-stack data scientist and taking solutions to production.
• Educational qualifications should be preferably in Computer Science, Statistics, Engineering or a related area.

• Demonstrate ability in NLP/ML/DL project solutions and architectures.
• Strong ability in developing NLP tool and end to end solutions.
• Minimum 1 year of experience in text cleaning, data wrangling, and text mining.
• Good understanding of Rule-based, statistical, and probabilistic NLP techniques.
• Collaborate with analytics team members to design, implement, and develop enterprise-level NLP capabilities, including data engineering, technology platforms, and algorithms.
• Good knowledge of NLP approaches and concepts like topic modelling, text summarization, semantic modelling, Named Entity recognition, etc.
• Evaluate and benchmark the performance of different NLP systems and provide guidance on metrics and best practices.
• Test and deploy promising solutions quickly, managing deadlines and deliverables while applying latest research and techniques.
• Collaborate with business stakeholders to effectively integrate and communicate analysis findings across NLP solutions.

Key Technical Skills:

• Hands on experience in building NLP models using different NLP libraries and toolkit like NLTK, Stanford NLP, TextBlob, OCR etc.
• Strong programming skills in Python
• Good to have programming skill: Java/Scala/C/C++.
• Strong problem solving, logical and communication skills.

Tags: Natural Language Processing (NLP), Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Toolkit (NLTK), Analytics

Machine Learning Engineer

Location: Ahmedabad / Pune
Team: Technology

Company Profile
InFoCusp is a company working in the broad field of Computer Science, Software Engineering, and Artificial Intelligence (AI). It is headquartered in Ahmedabad, India, having a branch office in Pune.
We have worked on / are working on AI projects / algorithms-heavy projects with applications ranging in finance, healthcare, e-commerce, legal, HR/recruiting, pharmaceutical, leisure sports and computer gaming domains. All of this is based on the core concepts of data science,
computer vision, machine learning (with emphasis on deep learning), cloud computing, biomedical signal processing, text and natural language processing, distributed systems, embedded systems and the Internet of Things.

PRIMARY RESPONSIBILITIES:
● Applying machine learning, deep learning, and signal processing on large datasets (Audio, sensors, images, videos, text) to develop models.
● Architecting large scale data analytics/modeling systems.
● Designing and programming machine learning methods and integrating them into our ML framework/pipeline.
● Analyzing data collected from various sources,
● Evaluate and validate the analysis with statistical methods. Also presenting this in a lucid form to people not familiar with the domain of data science/computer science.
● Writing specifications for algorithms, reports on data analysis, and documentation of algorithms.
● Evaluating new machine learning methods and adapting them for our
purposes.
● Feature engineering to add new features that improve model
performance.

KNOWLEDGE AND SKILL REQUIREMENTS:
● Background and knowledge of recent advances in machine learning, deep learning, natural language processing, and/or image/signal/video processing with at least 3 years of professional work experience working on real-world data.
● Strong programming background, e.g. Python, C/C++, R, Java, and knowledge of software engineering concepts (OOP, design patterns).
● Knowledge of machine learning libraries Tensorflow, Jax, Keras, scikit-learn, pyTorch. Excellent mathematical skills and background, e.g. accuracy, significance tests, visualization, advanced probability concepts
● Ability to perform both independent and collaborative research.
● Excellent written and spoken communication skills.
● A proven ability to work in a cross-discipline environment in defined time frames. Knowledge and experience of deploying large-scale systems using distributed and cloud-based systems (Hadoop, Spark, Amazon EC2, Dataflow) is a big plus.
● Knowledge of systems engineering is a big plus.
● Some experience in project management and mentoring is also a big plus.

EDUCATION:
- B.E.\B. Tech\B.S. candidates' entries with significant prior experience in the aforementioned fields will be considered.
- M.E.\M.S.\M. Tech\PhD preferably in fields related to Computer Science with experience in machine learning, image and signal processing, or statistics preferred.

 

 

What you need to have:

 

What you need to have:

 

Key Skills
o Convert machine learning models into APIs for applications accessibility
o Running machine learning tests and experiments
o Implementing appropriate ML algorithms
o Creating machine learning models and retraining systems
o Study and transform data science prototypes
o Design machine learning systems
o Research and implement appropriate ML algorithms and tools
o Train and retrain systems when necessary
o Test and deploy models
o Use AI to empower the company with novel capabilities
o Designing and developing machine learning and deep learning system
o Outstanding analytical and problem-solving skills
• Alexa
o Excellent in Python programming
o Experience with AWS Lamda
o Experience with Alexa skills
o Alexa skill directives
• Google
o Excellent in NodeJS programming
o Experience with GCP - Dialog Flow and Actions on Google
o Using built-in intents and developing custom intents
o API integration and Postman knowledge

Instart Logic is the world’s first endpoint-aware application delivery solution that makes websites and applications fast, secure, and easy to operate. Instart Logic’s platform combines machine learning, virtualization, and open APIs with a content delivery network (CDN) for global delivery. Using Instart Logic, organizations like Kate Spade, Office Depot, and Washington Post can provide ultra-fast, visually immersive and secure experiences on any device to maximize revenue, deliver superior customer experiences, and gain competitive advantage. Instart Logic is funded by Andreessen Horowitz, Greylock, Kleiner Perkins, Stanford, Telstra, and several other notable Silicon Valley investors. You: Have you had a desire to Innovate and work on game changing disruptions in propelling a faster internet? Have you had a desire to contribute and ship code to production and get real time feedback on how your feature is performing? Have a desire to solve some of the most challenging problems in computer science? Have a desire to work with and learn from team of very high calibre computer scientists and researchers in an environment that fosters teamwork and creativity? Have a desire to publish your work in leading academic journals and industry conferences? If you answered YES to any of the above, you can start filling your look ahead buffer!

(Senior) Data Scientist Job Description

About us
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 a Master's degree and 1+ years of experience working on problems in NLP or Computer Vision.

If you have 4+ years of relevant experience with a Master's degree (PhD preferred), you will be considered for a senior role.

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.