Company Overview:
At Codvo, software and people transformations go hand-in-hand. We are a global empathyled technology services company. Product innovation and mature software engineering are part of our core DNA. Respect, Fairness, Growth, Agility, and Inclusiveness are the core values that we aspire to live by each day. We continue to expand our digital strategy, design, architecture, and product management capabilities to offer expertise, outside-the-box thinking, and measurable results.
Required Skills (Technical):
- Advanced knowledge of statistical techniques, NLP, machine learning algorithms and deep learning frameworks like TensorFlow, Theano, Kera’s, Pytorch.
- Proficiency with modern statistical modelling (regression, boosting trees, random forests, etc.), machine learning (text mining, neural network, NLP, etc.), optimization (linear optimization, nonlinear optimization, stochastic optimization, etc.) methodologies.
- Building complex predictive models using ML and DL techniques with production quality code and jointly own complex data science workflows with the Data Engineering team.
- Familiarity with modern data analytics architecture and data engineering technologies (SQL and No-SQL databases).
- Knowledge of REST APIs and Web Services
- Experience with Python, R, sh/bash
Required Skills (Non-Technical):
- Fluent in English Communication (Spoken and verbal)
- Should be a team player
- Should have a learning aptitude
- Detail-oriented, analytically.
- Extremely organized with strong time-management skills
- Problem Solving & Critical Thinking
About Codvoai
At Codvo, we accelerate Cloud, AI, and Transformation roadmaps while offering most satisfying mix of work-life balance, quality of living, and cutting edge work to our employees.
We deliver value through our unique "Virtual Silicon Valley" model where we bring seasoned experts and global talent together as a Product Oriented Deliver (POD) unit to successfully deliver on your next roadmap priorities.
Our “Virtual Silicon Valley” PODs deliver better success and speed because they are self-managed, have right expertise mix, and most importantly are aligned to work in your time zone. The goal is to balance speed, expertise mix, and cost while ensuring the success of core product development, design, and transformation activities.
We are proud to have our customers ready to vouch for us and share their success stories. Our teams of scientists, engineers, architects, and designers have helped AI-driven companies, fast-growing Fintechs, Wealth Management & Healthcare startups, Energy companies, and US Defense contractors accelerate their product and transformation roadmaps.
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Duties and Responsibilities:
Research and Develop Innovative Use Cases, Solutions and Quantitative Models
Quantitative Models in Video and Image Recognition and Signal Processing for cloudbloom’s
cross-industry business (e.g., Retail, Energy, Industry, Mobility, Smart Life and
Entertainment).
Design, Implement and Demonstrate Proof-of-Concept and Working Proto-types
Provide R&D support to productize research prototypes.
Explore emerging tools, techniques, and technologies, and work with academia for cutting-
edge solutions.
Collaborate with cross-functional teams and eco-system partners for mutual business benefit.
Team Management Skills
Academic Qualification
7+ years of professional hands-on work experience in data science, statistical modelling, data
engineering, and predictive analytics assignments
Mandatory Requirements: Bachelor’s degree with STEM background (Science, Technology,
Engineering and Management) with strong quantitative flavour
Innovative and creative in data analysis, problem solving and presentation of solutions.
Ability to establish effective cross-functional partnerships and relationships at all levels in a
highly collaborative environment
Strong experience in handling multi-national client engagements
Good verbal, writing & presentation skills
Core Expertise
Excellent understanding of basics in mathematics and statistics (such as differential
equations, linear algebra, matrix, combinatorics, probability, Bayesian statistics, eigen
vectors, Markov models, Fourier analysis).
Building data analytics models using Python, ML libraries, Jupyter/Anaconda and Knowledge
database query languages like SQL
Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM,
Decision Forests.
Strong Math Skills (Multivariable Calculus and Linear Algebra) - understanding the
fundamentals of Multivariable Calculus and Linear Algebra is important as they form the basis
of a lot of predictive performance or algorithm optimization techniques.
Deep learning : CNN, neural Network, RNN, tensorflow, pytorch, computervision,
Large-scale data extraction/mining, data cleansing, diagnostics, preparation for Modeling
Good applied statistical skills, including knowledge of statistical tests, distributions,
regression, maximum likelihood estimators, Multivariate techniques & predictive modeling
cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis
Experience with Data Visualization Tools like Tableau, Power BI, Qlik Sense that help to
visually encode data
Excellent Communication Skills – it is incredibly important to describe findings to a technical
and non-technical audience
Capability for continuous learning and knowledge acquisition.
Mentor colleagues for growth and success
Strong Software Engineering Background
Hands-on experience with data science tools
As an Associate Manager - Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve
predefined outcomes.
• Engage with clients to understand current and future business goals and translate business
problems into analytical frameworks
• Develop custom models based on an in-depth understanding of underlying data, data structures,
and business problems to ensure deliverables meet client needs
• Create repeatable, interpretable and scalable models
• Effectively communicate the analytics approach and insights to a larger business audience
• Collaborate with team members, peers and leadership at Tredence and client companies
Qualification:
1. Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics,
statistics) or equivalent experience.
2. 5+ years of experience in data science, building hands-on ML models
3. Experience leading the end-to-end design, development, and deployment of predictive
modeling solutions.
4. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data
analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc.
5. Advanced SQL skills with SQL Server and Spark experience.
6. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms
(Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks
7. Experience with Natural Language Processing (NLTK) and text analytics for information
extraction, parsing and topic modeling.
8. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills.
Thrive in a fast-paced, innovative environment
9. Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred
10. Experience with cloud platforms such as Azure, AWS is preferred but not required
Key deliverables for the Data Science Engineer would be to help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver even better products. Your primary focus will be on applying data mining techniques, doing statistical analysis, and building high-quality prediction systems integrated with our products.
What will you do?
- You will be building and deploying ML models to solve specific business problems related to NLP, computer vision, and fraud detection.
- You will be constantly assessing and improving the model using techniques like Transfer learning
- You will identify valuable data sources and automate collection processes along with undertaking pre-processing of structured and unstructured data
- You will own the complete ML pipeline - data gathering/labeling, cleaning, storage, modeling, training/testing, and deployment.
- Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
- Building predictive models and machine-learning algorithms to apply to data sets.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Presenting information using data visualization techniques and proposing solutions and strategies to business challenges
We would love to hear from you if :
- You have 2+ years of experience as a software engineer at a SaaS or technology company
- Demonstrable hands-on programming experience with Python/R Data Science Stack
- Ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python
- Familiarity with Big Data Platforms (Databricks, Hadoop, Hive), AWS Services (AWS, Sagemaker, IAM, S3, Lambda Functions, Redshift, Elasticsearch)
- Experience in Probability and Statistics, ability to use ideas of Data Distributions, Hypothesis Testing and other Statistical Tests.
- Demonstrable competency in Data Visualisation using the Python/R Data Science Stack.
- Preferable Experience Experienced in web crawling and data scraping
- Strong experience in NLP. Worked on libraries such as NLTK, Spacy, Pattern, Gensim etc.
- Experience with text mining, pattern matching and fuzzy matching
Why Tartan?
- Brand new Macbook
- Stock Options
- Health Insurance
- Unlimited Sick Leaves
- Passion Fund (Invest in yourself or your passion project)
- Wind Down
Do you want to help build real technology for a meaningful purpose? Do you want to contribute to making the world more sustainable, advanced and accomplished extraordinary precision in Analytics?
What is your role?
As a Computer Vision & Machine Learning Engineer at Datasee.AI, you’ll be core to the development of our robotic harvesting system’s visual intelligence. You’ll bring deep computer vision, machine learning, and software expertise while also thriving in a fast-paced, flexible, and energized startup environment. As an early team member, you’ll directly build our success, growth, and culture. You’ll hold a significant role and are excited to grow your role as Datasee.AI grows.
What you’ll do
- You will be working with the core R&D team which drives the computer vision and image processing development.
- Build deep learning model for our data and object detection on large scale images.
- Design and implement real-time algorithms for object detection, classification, tracking, and segmentation
- Coordinate and communicate within computer vision, software, and hardware teams to design and execute commercial engineering solutions.
- Automate the workflow process between the fast-paced data delivery systems.
What we are looking for
- 1 to 3+ years of professional experience in computer vision and machine learning.
- Extensive use of Python
- Experience in python libraries such as OpenCV, Tensorflow and Numpy
- Familiarity with a deep learning library such as Keras and PyTorch
- Worked on different CNN architectures such as FCN, R-CNN, Fast R-CNN and YOLO
- Experienced in hyperparameter tuning, data augmentation, data wrangling, model optimization and model deployment
- B.E./M.E/M.Sc. Computer Science/Engineering or relevant degree
- Dockerization, AWS modules and Production level modelling
- Basic knowledge of the Fundamentals of GIS would be added advantage
Prefered Requirements
- Experience with Qt, Desktop application development, Desktop Automation
- Knowledge on Satellite image processing, Geo-Information System, GDAL, Qgis and ArcGIS
About Datasee.AI:
Datasee>AI, Inc. is an AI driven Image Analytics company offering Asset Management solutions for industries in the sectors of Renewable Energy, Infrastructure, Utilities & Agriculture. With core expertise in Image processing, Computer Vision & Machine Learning, Takvaviya’s solution provides value across the enterprise for all the stakeholders through a data driven approach.
With Sales & Operations based out of US, Europe & India, Datasee.AI is a team of 32 people located across different geographies and with varied domain expertise and interests.
A focused and happy bunch of people who take tasks head-on and build scalable platforms and products.
About us: Nexopay helps transforming digital payments and enabling instant financing for parents, across schools and colleges world-wide.
Responsibilities:
- Work with stakeholders throughout the organisation and across entities to identify opportunities for leveraging internal and external data to drive business impact
- Mine and analyze data to improve and optimise performance, capture meaningful insights and turn them into business advantages
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Develop custom data models and algorithms to apply to data sets
- Use predictive modeling to predict outcomes and identify key drivers
- Coordinate with different functional teams to implement models and monitor outcomes
- Develop processes and tools to monitor and analyze model performance and data accuracy
Requirements:
- Experience in solving business problem using descriptive analytics, statistical modelling / machine learning
- 2+ years of strong working knowledge of SQL language
- Experience with visualization tools e. g., Tableau, Power BI
- Working knowledge on handling analytical projects end to end using industry standard tools (e. g., R, Python)
- Strong presentation and communication skills
- Experience in education sector is a plus
- Fluency in English
- 3+ years of experience in Machine Learning
- Bachelors/Masters in Computer Engineering/Science.
- Bachelors/Masters in Engineering/Mathematics/Statistics with sound knowledge of programming and computer concepts.
- 10 and 12th acedemics 70 % & above.
Skills :
- Strong Python/ programming skills
- Good conceptual understanding of Machine Learning/Deep Learning/Natural Language Processing
- Strong verbal and written communication skills.
- Should be able to manage team, meet project deadlines and interface with clients.
- Should be able to work across different domains and quickly ramp up the business processes & flows & translate business problems into the data solutions
Job Description
Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.
Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.
Experience
10+ Years
Location
Bozeman/Hyderabad
Skills
Required Skills:
Bachelors/Masters or Phd in Computer Science or related industry experience
3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow
7+ Years of industry experience in scripting languages such as Python, R.
7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing
Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc
Some experience in setting up large scale training data pipelines.
Some experience in using Cloud services such as AWS, GCP, Azure
Desired Skills:
Experience in building deep learning models for Computer Vision and Natural Language Processing domains
Experience in productionizing/serving machine learning in industry setting
Understand the principles of developing cloud native applications
Responsibilities
Collect, Organize and Process data pipelines for developing ML models
Research and develop novel prototypes for customers
Train, implement and evaluate shippable machine learning models
Deploy and iterate improvements of ML Models through feedback
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 [email protected]
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.
