Couture AI Platform provides Pluggable Building Blocks to the entire AI stack, which is used to build and produce varied enterprise ML and deep learning use cases. It has enabled some of the largest global organizations to implement specific vertical targeted products build on top of its proprietary AI platform. Experience: Building large scale AI models and/or systems. Expertise with Data, Machine Learning, and Deep Learning (CNN, RNN, LSTM, RBM, Seq-to-Seq Autoencoders Decoders, etc.). Strong data structures and algorithms capabilities. Looking for data science researchers. Strong working knowledge of deep learning, machine learning, and statistics. - Domain understanding of Personalization, Search, and Visual. Strong math skills with statistical modeling and machine learning. Experience in using Python, statistical/machine learning libs. Hands-on experience building models with deep learning frameworks (TensorFlow & TF tooling: TFX, TF Serving, Tensor Board, etc.). Ability to think creatively and solve problems. Preferred: Publications in highly accredited journals (If available, please share links to your published work.).Or, history of scaling ML/Deep learning algorithms at a massively large scale.
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. upGrad was awarded the Best Tech for Education by IAMAI for 2018-19 upGrad was also ranked as one of the LinkedIn Top Startups 2018: The 25 most sought- after startups in India upGrad was earlier selected as one of the top ten most innovative companies in India by FastCompany. We were also covered by the Financial Times along with other disruptors in Ed-Tech upGrad is the official education partner for Government of India - Startup India program 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 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 technique
Associate Director – Data ScienceTiger Analytics is a global AI & analytics consulting firm. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modeled around expertise and mutual respect with a team first mindset. Working at Tiger, you’ll be at the heart of this AI revolution. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire.We are headquartered in the Silicon Valley and have our delivery centres across the globe. The below role is for our Chennai or Bangalore office, or you can choose to work remotely.About the Role:As an Associate Director - Data Science at Tiger Analytics, you will lead data science aspects of endto-end client AI & analytics programs. Your role will be a combination of hands-on contribution, technical team management, and client interaction.• Work closely with internal teams and client stakeholders to design analytical approaches tosolve business problems• Develop and enhance a broad range of cutting-edge data analytics and machine learningproblems across a variety of industries.• Work on various aspects of the ML ecosystem – model building, ML pipelines, logging &versioning, documentation, scaling, deployment, monitoring and maintenance etc.• Lead a team of data scientists and engineers to embed AI and analytics into the clientbusiness decision processes.Desired Skills:• High level of proficiency in a structured programming language, e.g. Python, R.• Experience designing data science solutions to business problems• Deep understanding of ML algorithms for common use cases in both structured andunstructured data ecosystems.• Comfortable with large scale data processing and distributed computing• Excellent written and verbal communication skills• 10+ years exp of which 8 years of relevant data science experience including hands-onprogramming.Designation will be commensurate with expertise/experience. Compensation packages among the best in the industry.
In this role, we are looking for: A problem-solving mindset with the ability to understand business challenges and how to apply your analytics expertise to solve them. The unique person who can present complex mathematical solutions in a simple manner that most will understand, using data visualization techniques to tell a story with data. An individual excited by innovation and new technology and eager to finds ways to employ these innovations in practice. A team mentality, empowered by the ability to work with a diverse set of individuals. A passion for data, with a particular emphasis on data visualization. Basic Qualifications A Bachelor’s degree in Data Science, Math, Statistics, Computer Science or related field with an emphasis on data analytics. 5+ Years professional experience, preferably in a data analyst / data scientist role or similar, with proven results in a data analyst role. 3+ Years professional experience in a leadership role guiding high-performing, data-focused teams with a track record of building and developing talent. Proficiency in your statistics / analytics / visualization tool of choice, but preferably in the Microsoft Azure Suite, including PowerBI and/or AzureML.
Computer vision engineerJob descriptionArtelus is an AI healthcare product company that is bringing healthcare to billions using deep learning.We are working in the Deep Learning space to solve healthcare problems. We seek to make products, which would complement the knowledgeand assist the clinician in making faster and accurate diagnoses.We are leveraging cutting-edge technologies like Deep Learning and artificial intelligence to increase the capacity of healthcare providersenabling them to offer higher quality care without overburdening the system.Solutions using Deep Learning Algorithms have a higher rate of accuracy and early detection can save lives.We are looking for creators who can build products that our customers love. The challenge for you will involve understanding, and building for, anunforgiving consumer who invests a lot of trust into the product YOU will build. Your product will be used by thousands.You'll be responsible for:Writing quality code using language best practicesWorking in a highly collaborative teamBuilding good software using the latest tools and techniquesParticipating in design reviews, coding modules, code reviews, and unit testingTaking ownership of the quality and usability of your codeRequirementsYou are an expert in computer vision algorithms - segmentation, homographyYou are an expert in image processing algorithms - morphology, filtering, enhancementYou are good in deep learning - classification, segmentationYou possess good enough knowledge of Linear algebraYou are aware of recent developments in deep learningYou have developed Image classification and segmentation models using deep learningYou are an expert in Python, OpenCV, TensorflowYou have worked with Numpy, Pandas, etcYou must have worked for 3+ years in building computer vision applicationsYou can use GIT wellYou are an open-source contributorYou have completed BTech in CSE/ECE/EEEYou have published papers in international conferences (OPTIONAL)We Value:Entrepreneurial spirit. Everywhere you go, you can’t help but mobilize people, build things, solve problems, roll up your sleeves, goabove and beyond, raise the bar. You are an insatiable doer and driver.Strong execution and organization. Your team will be working with engineers and product leads at the bleeding edge of the developmentcycle. To be successful in this role, you should be comfortable executing with little oversight and be able to adapt to problems quicklyStrategic mindset - you’re comfortable thinking a few steps ahead of where the team is at nowWhat you’ll get:Very competitive salary with performance bonusActive promotion of your professional career by sending you to events, hackathons, user groups, etc.Weekly time-slot where you are encouraged to spend time to play around with new technology or self-learning
Responsibilities Design experiments, test hypotheses, and build models utilizing the traditional datasets and graph data. Apply advanced statistical and predictive modeling techniques to build, maintain, and improve on multiple real-time decision systems. Identify what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as geo-location or social media Utilize patterns and variations in the volume, speed and other characteristics of data for predictive analysis. Define the preprocessing or feature engineering to be done on a given dataset, data augmentation pipelines, training models and tuning their hyperparameters, analyzing the errors of the model and designing strategies to overcome them Selecting features, building and optimizing classifiers using machine learning techniques Extending the company’s data with third party sources of information when needed Creating automated anomaly detection systems and constant tracking of its performance Skills and Qualifications Bachelors in mathematics, statistics or computer science or a related field; Masters or PHD degree preferred. Experience with one or two of the following: Deep Learning methods, NLP, computer vision, sentiment analysis, topic modeling and graph theory and databases Experience with common data science tools such as Python, R, PyTorch, TensorFlow, Keras, NLTK, Spacy, or Neo4j, and a good understanding of modelling platforms (Azure AutoML, SageMaker, DataBricks, DataRobot, and H2O.ai) Experience working with big data distributed programming languages, and ecosystems: Spark, Hadoop, MapReduce, Pig, Kafka Familiarity with Cloud-based environments such as AWS (S3/EC2), Azure, Google Cloud Experience with building and deploying predictive and prescriptive analytics models Ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets. Demonstrable ability to quickly understand new concepts-all the way down to the theorems- and to come out with original solutions to mathematical issues. Strong communication and interpersonal skills
Looking for senior data science researchers. Basic Qualifications: ∙Bachelors in Computer Science/Mathematics + Research (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from Tier1 tech institutes. ∙3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems. ∙1 year or more of experience specifically with deep learning (CNN, RNN, LSTM, RBM etc). ∙Strong working knowledge of deep learning, machine learning, and statistics. - Deep domain understanding of Personalization, Search and Visual. ∙Strong math skills with statistical modeling / machine learning. ∙Hands-on experience building models with deep learning frameworks like MXNet or Tensorflow. ∙Experience in using Python, statistical/machine learning libs. ∙Ability to think creatively and solve problems. ∙Data presentation skills. Preferred: ∙MS/ Ph.D. (Machine Learning, Deep Learning, Statistics, Data Mining, Game Theory or core mathematical areas) from IISc and other Top Global Universities. ∙Or, Publications in highly accredited journals (If available, please share links to your published work.). ∙Or, history of scaling ML/Deep learning algorithm at massively large scale.
About the Opportunity We are looking for a trailblazer & practitioner Data Scientist to lead the initiatives we’re taking, to improve the product offerings of Blackhawk Network, from the perspective of risk modelling and business forecasting (prescriptive & predictive). As a Senior Data Scientist, you will own the research charter for Data & Decision Science, to enable the business stakeholders to be data-driven and deterministic, by providing insights into the decisions at-hand and also roadmap planning. You will be the Senior member in a team of Data Scientists to provide mentorship and enable a culture of 360-degree analysis of business, with ownership of the Modelling Environments and Risk Engines. You will get the support to evangelise sound practices for prototyping of concepts, to fail-fast and/or maintain continuum of persistent research. You will collaborate with multi-disciplinary teams of engineers, product owners & business stakeholders to solve complex & ambiguous problems, in the domains of: Gift Cards E-Commerce (B2B & B2C) Forecasting of Inventory, Traffic & Breakage Risk Modelling (Scorecards) Fraud Detection & Prevention Loyalty & Rewards Programs Modelling Requirements A strong background in advanced mathematics, in particular statistics & probability theory, data mining, and machine learning. 10+ years of overall professional experience, with 5+ years in data science, doing exploratory data analysis, testing hypotheses, and building prescriptive & predictive models. Masters (or equivalent) degree in a quantitative discipline (Statistics, Operations Research, Data Science, Mathematics, Physics, Engineering etc.). Proficiency in a programming language of your own choice (Python, R, Matlab, etc.), and previous experience efficiently conducting research and creating on-demand reports. Strong Communication: ability to articulate clearly, navigate & adapt across different seniority levels. Ability to use statistical, algorithmic, data mining, and visualization techniques to model complex problems, find opportunities, discover solutions, and deliver actionable business insights. An excellent ability to learn new programming languages quickly and optimally. Be passionate about collaborating daily with your team and other groups while working via a distributed multi-geo global operating model. Be eager to help your teammates, share your knowledge with them, and learn from them. Ability to work with large, complex data sets to produce insights & results. Big pluses include significant experience managing or shipping out a product, leading a team, and working on open source projects.
** Responsibilities:** Translating the state of the art research results into real-world production systems. Lead your project, from feasibility assessment and research through to model development and productionization. Coaching team members and provide training paths, encourage and implement best practices across the team. Have prior experience of leading a computer vision project from scratch designing, planning, data collection and annotation, training, deployment and iteration phases. Required Skill Set : Proficiency in Python/C++, Open CV and deep learning frameworks like Pytorch Experience in scaling the AI capabilities in a high volume, high scalability environment Hands-on experience in CI/CD workflow, version controls and code reviews. Well versed in taking a computer vision project through the planning, data collection + annotation, training, deployment and iteration phases Bachelors, Masters or PhD in computer science, Machine learning or equivalent from a tier 1 college is preferred. Expertise in one or more of the following: object detection, semantic segmentation, OCR and forgery detection Publications and patents in the computer vision field are preferred Desired Experience: 6+ years of professional experience on computer vision and / or deep learning Prior experience of leading an AI product development Experience in scaling the AI capabilities in a high volume, high scalability environment Building & scaling computer vision teams & computer vision infrastructure as well. Design & development of DL algorithm and experimentation to improve existing computer vision systems. Bonus point if prior experience from fintech domain or other product based companies.
Work-days: Sunday through ThursdayWork shift: Day time Strong problem-solving skills with an emphasis on product development. • Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and drawinsights from large data sets.• Experience in building ML pipelines with Apache Spark, Python• Proficiency in implementing end to end Data Science Life cycle• Experience in Model fine-tuning and advanced grid search techniques• Experience working with and creating data architectures.• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neuralnetworks, etc.) and their real-world advantages/drawbacks.• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions,statistical tests and proper usage, etc.) and experience with applications.• Excellent written and verbal communication skills for coordinating across teams.• A drive to learn and master new technologies and techniques.• 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 increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.• Develop company A/B testing framework and test model quality.• Coordinate with different functional teams to implement models and monitor outcomes.• Develop processes and tools to monitor and analyze model performance and data accuracy.Key skills:● Strong knowledge in Data Science pipelines with Python● Object-oriented programming● A/B testing framework and model fine-tuning● Proficiency in using sci-kit, NumPy, and pandas package in pythonNice to have:● Ability to work with containerized solutions: Docker/Compose/Swarm/Kubernetes● Unit testing, Test-driven development practice● DevOps, Continuous integration/ continuous deployment experience● Agile development environment experience, familiarity with SCRUM● Deep learning knowledge
B.Tech/MTech from tier 1 institution 8+years of experience in machine learning techniques like logistic regression, random forest, boosting, trees, neural networks, etc. Showcased experience with Python, SQL and proficiency in Scikit Learn, Pandas, NumPy, Keras and TensorFlow/pytorch Experience of working with Qlik sense or Tableau is a plus Experience of working in a product company is a plus
2 to 4 years of relevant industry experience Experience in Linear algebra, statistics & Probability skills, such as distributions, Deep Learning, Machine Learning Strong mathematical and statistics background is a must Experience in machine learning frameworks such as Tensorflow, Caffe, PyTorch, or MxNet Strong industry experience in using design patterns, algorithms and data structures Industry experience in using feature engineering, model performance tuning, and optimizing machine learning models Hands on development experience in Python and packages such as NumPy, Sci-Kit Learn and Matplotlib Experience in model building, hyper parameter tuning and optimization.
Must have Skills: Extract and present valuable information from data Understand business requirements and generate insights Build mathematical models, validate and work with them Explain complex topics tailored to the audience Validate and follow up on results Work with large and complex data sets Establish priorities with clear goals and responsibilities to achieve a high level of performance. Work in an agile and iterative manner on solving problems Evaluate different options proactively and the ability to solve problems in an innovative way. Develop new solutions or combine existing methods to create new approaches. Good understanding of Digital & analytics Strong communication skills, orally and in writing Job Overview:As a Data Scientist you will work in collaboration with our business and engineering people, on creating value from data. Often the work requires solving complex problems by turning vast amounts of data into business insights through advanced analytics, modeling and machine learning. You have a strong foundation in analytics, mathematical modeling, computer science, and math - coupled with a strong business sense. You proactively fetch information from various sources and analyze it for better understanding about how the business performs. Furthermore, you model and build AI tools that automate certain processes within the company. The solutions produced will be implemented to impact business results. The Data Scientist believes in a non-hierarchical culture of collaboration, transparency, safety, and trust. Working with a focus on value creation, growth and serving customers with full ownership and accountability. Delivering exceptional customer and business results Industry: Any (prefer – Manufacturing, Logistics); willingness to learn manufacturing systems (OT systems and data stores)Primary Responsibilities: Develop an understanding of business obstacles, create solutions based on advanced analytics and draw implications for model development Combine, explore, and draw insights from data. Often large and complex data assets from different parts of the business. Design and build explorative, predictive- or prescriptive models, utilizing optimization, simulation, and machine learning techniques Prototype and pilot new solutions and be a part of the aim of ‘productifying’ those valuable solutions that can have an impact at a global scale Guides and coaches other chapter colleagues to help solve data/technical problems at an operational level, and in methodologies to help improve development processes Identifies and interprets trends and patterns in complex data sets to enable the business to make data-driven decisions Regards, Sudarshini
Important:Credit Score is mandatory.You are expected to build deep learning models to process unstructured data like images and scanned financial documents and convert it into meaningful tables with optical character recognition technologies.You are also expected to build Machine Learning and Deep learning models for facial recognition and object comparison.The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in thefield.JD To build deep learning models in Tensorflow and Keras To build Machine learning and Text Analysis projects Extensive knowledge of python, data structures, and algorithms Responsibilities Selecting features, building and optimizing classifiers using machine learning techniques Processing, cleansing, and verifying the integrity of data used for analysis Doing ad-hoc Data Analysis analysis and presenting results in a clear manner Building Deep learning models over unstructured sources such as images, speech and text data. Skills and Qualifications B.E/B.TECH/MCA in COMPUTER SCIENCE ENGINEERING ONLY or Any Degree specializing in Computer Science or Information Technology or Information Science. Excellent Knowledge of computer science engineering basics. Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc Understanding of Natural Language processing techniques and algorithms such as dimensionality reduction, NLTK, CoreNLP, Spacy Understanding of Deep learning concepts and techniques such as YoLo, Object Detection, Image Classification. Experience with common data science toolkits, such as scikit-learn, spacy, Keras. Excellence in at least one of these is highly desirable Great communication skills in English both written and verbal. Proficiency in using query languages such as SQL. Good applied statistics skills, such as distributions, statistical testing, regression, etc. Good programming skills in Python or Java. Well versed with data structures and algorithms. Deep learning & Machine learning