business analytics

Roles and Responsibilities
● Research and develop advanced statistical and machine learning models for
analysis of large-scale, high-dimensional data.
● Dig deeper into data, understand characteristics of data, evaluate alternate
models and validate hypothesis through theoretical and empirical approaches.
● Productize proven or working models into production quality code.
● Collaborate with product management, marketing and engineering teams in
Business Units to elicit & understand their requirements & challenges and
develop potential solutions
● Stay current with latest research and technology ideas; share knowledge by
clearly articulating results and ideas to key decision makers.
● File patents for innovative solutions that add to company's IP portfolio

Requirements
● 4 to 6 years of strong experience in data mining, machine learning and
statistical analysis.
● BS/MS/PhD in Computer Science, Statistics, Applied Math, or related areas
from Premier institutes (only IITs / IISc / BITS / Top NITs or top US university
should apply)
● Experience in productizing models to code in a fast-paced start-up
environment.
● Expertise in Python programming language and fluency in analytical tools
such as Matlab, R, Weka etc.
● Strong intuition for data and Keen aptitude on large scale data analysis

● Strong communication and collaboration skills.

Job Description

We are looking for an experienced engineer to join our data science team, who will help us design, develop, and deploy machine learning models in production. You will develop robust models, prepare their deployment into production in a controlled manner, while providing appropriate means to monitor their performance and stability after deployment.

 

What You’ll Do will include (But not limited to):

• Preparing datasets needed to train and validate our machine learning models
• Anticipate and build solutions for problems that interrupt availability, performance, and stability in our systems, services, and products at scale.
• Defining and implementing metrics to evaluate the performance of the models, both for computing performance (such as CPU & memory usage) and for ML performance (such as precision, recall, and F1)
• Supporting the deployment of machine learning models on our infrastructure, including containerization, instrumentation, and versioning
• Supporting the whole lifecycle of our machine learning models, including gathering data for retraining, A/B testing, and redeployments
• Developing, testing, and evaluating tools for machine learning models deployment, monitoring, retraining.
• Working closely within a distributed team to analyze and apply innovative solutions over billions of documents
• Supporting solutions ranging from rule-bases, classical ML techniques  to the latest deep learning systems.
• Partnering with cross-functional team members to bring large scale data engineering solutions to production
• Communicating your approach and results to a wider audience through presentations

Your Qualifications:

• Demonstrated success with machine learning in a SaaS or Cloud environment, with hands–on knowledge of model creation and deployments in production at scale
• Good knowledge of traditional machine learning methods and neural networks
• Experience with practical machine learning modeling, especially on time-series forecasting, analysis, and causal inference.
• Experience with data mining algorithms and statistical modeling techniques for anomaly detection in time series such as clustering, classification, ARIMA, and decision trees is preferred.
• Ability to implement data import, cleansing and transformation functions at scale
• Fluency in Docker, Kubernetes
• Working knowledge of relational and dimensional data models with appropriate visualization techniques such as PCA.
• Solid English skills to effectively communicate with other team members

 

Due to the nature of the role, it would be nice if you have also:

• Experience with large datasets and distributed computing, especially with the Google Cloud Platform
• Fluency in at least one deep learning framework: PyTorch, TensorFlow / Keras
• Experience with No–SQL and Graph databases
• Experience working in a Colab, Jupyter, or Python notebook environment
• Some experience with monitoring, analysis, and alerting tools like New Relic, Prometheus, and the ELK stack
• Knowledge of Java, Scala or Go-Lang programming languages
• Familiarity with KubeFlow
• Experience with transformers, for example the Hugging Face libraries
• Experience with OpenCV

 

About Egnyte

In a content critical age, Egnyte fuels business growth by enabling content-rich business processes, while also providing organizations with visibility and control over their content assets. Egnyte’s cloud-native content services platform leverages the industry’s leading content intelligence engine to deliver a simple, secure, and vendor-neutral foundation for managing enterprise content across business applications and storage repositories. More than 16,000 customers trust Egnyte to enhance employee productivity, automate data management, and reduce file-sharing cost and complexity. Investors include Google Ventures, Kleiner Perkins, Caufield & Byers, and Goldman Sachs. For more information, visit www.egnyte.com

 

#LI-Remote

Founders are the alumnus of IIT-D, IIM-B and Wharton. They’ve 12+ years of experience as Venture capital and corporate entrepreneurship at DFJ, Vertex, InMobi and VP at Snyder UAE, investment banking at Unitus Capital - leading the financial services practice, and institutional equities at Kotak. They’ve a team of high-quality professionals coming together for this mission to disrupt the convention. AsData Scientist, you will develop a first of its kind risk engine for revenue-based financing in India and automating investment appraisals for the company's different revenue-based financing products

What you will do:

 

 

Desired Candidate Profile

 

What you need to have:

Responsibilities: 

• Improve robustness of Leena AI current NLP stack 
• Increase zero shot learning capability of Leena AI current NLP stack 
• Opportunity to add/build new NLP architectures based on requirements 
• Manage End to End lifecycle of the data in the system till it achieves more than 90% accuracy 
• Manage a NLP team 

Page BreakRequirements: 

• Strong understanding of linear algebra, optimisation, probability, statistics 
• Experience in the data science methodology from exploratory data analysis, feature engineering, model selection, deployment of the model at scale and model evaluation 
• Experience in deploying NLP architectures in production 
• Understanding of latest NLP architectures like transformers is good to have 
• Experience in adversarial attacks/robustness of DNN is good to have 
• Experience with Python Web Framework (Django), Analytics and Machine Learning frameworks like Tensorflow/Keras/Pytorch. 

1. Develop novel computer vision/NLP algorithms
2. Build large datasets that will be used to train the models
3. Empirically evaluate related research works
4. Train and evaluate deep learning architectures on multiple large scale datasets
5. Collaborate with the rest of the research team to produce high-quality research

APPLY LINK: http://bit.ly/2F83vxU Go through the entire job post thoroughly before pressing Apply. There is an eleven characters french word v*n*i*r*t*e mentioned somewhere in the whole text which is irrelevant to the context. You shall be required to enter this word while applying else application won't be considered submitted. ````````````````````````````````````````````````````````````````````````````````````````````````````` Researcher - Deep Learning & AI Team: Research Full-Time, Permanent Bangaluru, India Relevant Exp: 6 months - 5 Years Background: Top Tier institute + Startup exposure Compensation: INR 10-50 LPA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Busigence is a Decision Intelligence Company. We create decision intelligence products for real people by combining data, technology, business, and behavior enabling strengthened decisions. Scaling established startup by IIT alumni innovating & disrupting marketing domain through artificial intelligence. We bring those people onboard who are dedicated to deliver wisdom to humanity by solving the world’s most pressing problems differently thereby significantly impacting thousands of souls, everyday. We are a deep rooted organization with six years of success story having worked with folks from top tier background (IIT, NSIT, DCE, BITS, IIITs, NITs, IIMs, ISI etc.) maintaining an awesome culture with a common vision to build great data products. In past we have served fifty five customers and presently developing our second product, Robonate. First was emmoQ - an emotion intelligence platform. Third offering, H2HData, an innovation lab where we solve hard problems through data, science, & design. We work extensively & intensely on big data, data science, machine learning, deep learning, reinforcement learning, data analytics, natural language processing, cognitive computing, and business intelligence. First-and-Foremost Before you dive-in exploring this opportunity and press Apply, we wish you to evaluate yourself - We are looking for right candidate, not the best candidate. We love to work with someone who can mandatorily gel with our vision, beliefs, thoughts, methods, and values --- which are aligned with what can be expected in a true startup with ambitious goals. Skills are always secondary to us. Primarily, you must be someone who is not essentially looking for a job or career, rather starving for a challenge, you yourself probably don't know since when. A book can be written on what an applicant must have before joining a . For brevity, in nutshell, we need these three in you: 1. You must be [super sharp] (Just an analogue, but Irodov, Mensa, Feynman, Polya, ACM, NIPS, ICAAC, BattleCode, DOTA etc should have been your Done stuff. Can you relate solution 1 to problem 2? or Do you get confused even when solved similar problem in past? Are you able to grasp problem statement in one go? or get hanged?) 2. You must be [extremely energetic] (Do you raise eyebrows when asked to stretch your limits, both in terms of complexity or extra hours to put in? What comes first in your mind, let's finish it today or this can be done tomorrow too? Its Friday 10 PM at work -Tired?) 3. You must be [honourably honest] (Do you tell others what you think, or what they want to hear? Later is good for sales team for their customers, not for this role. Are you honest with your work? intrinsically with yourself first?) You know yourself the best. If not ask your loved ones and then decide. We clearly need exceedingly motivated people with entrepreneurial traits, not employee mindset - not at all. This is an immediate requirement. We shall have an accelerated interview process for fast closure - you would be required to be proactive and responsive. Real ROLE We are looking for researchers with real passion for deep learning. You would be required to work with our research team on several deep learning applications. Mandatory R1. Must know in-and-out of functional programming in Python with strong flair for data structures, linear algebra, & algorithms implementation R2. Must be able to apply state-of-art deep learning models to our existing research and develop entirely new methods, which are advanced & modern R3. Must have designed multiple deep learning techniques solving complex business scenarios preferably from marketing domain across industries R4. Must have designed proven pre-processing techniques on unstructured (image, audio, video, text, logs) and time-series data R5. Must have designed CNN, RNN (atleast three variants including LSTM), Auto Encoders, DBN, MLP, RBM R6. Must have tweaked & trained on deep learning architectures mainly AlexNet, ResNet, RCNN, GAN R7. Must have worked on classification, clustering, computer vision, speech recognition, text summarization, time-series analysis R8. Must have firm understanding of the underlying mathematics will be needed to adapt modelling techniques to fit the problem space with large data (10M+ entities) R9. Must be extremely strong working knowledge on Python scientific stack (NumPy, SciPy, Matplotlib, Scikit-learn, Pandas, Stats model, Seaborn, PyBrain) and atleast basic working knowledge on TensorFlow. R/ SAS/ SPSS etc are not acceptable. Preferred R10. Good to have knowledge and practical experience in application of Supervised Learning algorithms, Bayesian methods, Gaussian processes, Combinatorial optimization, Meta Learning, Transfer Learning, Convex optimization, Sparse methods, Kernel methods, Stochastic process, Statistical learning theory, and Approximate inference R11. Good to have working knowledge of first-class, high order, & pure functions, recurisons, lazy evaluations, and immutable data structures R12. Good to have worked on Tensorboard, Saving & Restoring models, Continue Training R13. Good to have worked on Keras on top of TensorFlow R14. Good to have worked on Reinforcement Learning and Generative Adverbial Networks R15. Great problem solver with extremely high curiosity on data processing & patterns Ideal YOU Y1. Degree in engineering, or any other data-heavy field at Bachelors/Masters/Ph.D level or above from a top tier institute Y2. Relevant experience of 0.5 - 5 years working on real-world problems in a research lab or a reputed company or a proven startup Y3. You are a fanatical implementer who love to spend time with findings & innovations, more than your loved ones Y4. You are true believer that human intelligence can be augmented through computer science & mathematics and your survival vinaigrette depends on getting the most from the data Y5. You are an entrepreneur mindset with ownership, intellectuality, & creativity as way to work. These are not fancy words, we mean it Actual WE W1. Real startup with Meaningful products W2. Revolutionary not just disruptive W3. Rules creators not followers W4. Small teams with real brains not herd of blockheads W5. Completely trust us and should be trusted back Why Us In addition to the regular stuff which every good startup offers – Lots of learning, Food, Parties, Open culture, Flexible working hours, and what not…. We offer you: You shall be working on our revolutionary products which are pioneer in their respective categories. This is a fact. We try real hard to hire fun loving crazy folks who are driven by more than a paycheck. You shall be working with creamiest talent on extremely challenging problems at most happening workplace. How to Apply You should apply online by clicking "Apply Now". For queries regarding an open position, please write to [email protected] For more information, visit http://www.busigence.com Careers: http://careers.busigence.com Research: http://research.busigence.com Jobs: http://careers.busigence.com/jobs/research Feel right fit for the position, mandatorily attach PDF resume highlighting your A. Key Skills B. Knowledge Inputs C. Major Accomplishments D. Problems Solved E. Submissions – Github/ StackOverflow/ Kaggle/ Euler Project etc. (if applicable) If you don't see this open position that interests you, join our Talent Pool and let us know how you can make a difference here. Referrals are more than welcome. Keep us in loop.

We’re looking to hire someone to help scale Machine Learning and NLP efforts at Episource. You’ll work with the team that develops the models powering Episource’s product focused on NLP driven medical coding. Some of the problems include improving our ICD code recommendations , clinical named entity recognition and information extraction from clinical notes.

This is a role for highly technical machine learning & data engineers who combine outstanding oral and written communication skills, and the ability to code up prototypes and productionalize using a large range of tools, algorithms, and languages. Most importantly they need to have the ability to autonomously plan and organize their work assignments based on high-level team goals.

You will be responsible for setting an agenda to develop and ship machine learning models that positively impact the business, working with partners across the company including operations and engineering. You will use research results to shape strategy for the company, and help build a foundation of tools and practices used by quantitative staff across the company.

What you will achieve:

• Define the research vision for data science, and oversee planning, staffing, and prioritization to make sure the team is advancing that roadmap

• Invest in your team’s skills, tools, and processes to improve their velocity, including working with engineering counterparts to shape the roadmap for machine learning needs

• Hire, retain, and develop talented and diverse staff through ownership of our data science hiring processes, brand, and functional leadership of data scientists

• Evangelise machine learning and AI internally and externally, including attending conferences and being a thought leader in the space

• Partner with the executive team and other business leaders to deliver cross-functional research work and models

Required Skills:

• Strong background in classical machine learning and machine learning deployments is a must and preferably with 4-8 years of experience

• Knowledge of deep learning & NLP

• Hands-on experience in TensorFlow/PyTorch, Scikit-Learn, Python, Apache Spark & Big Data platforms to manipulate large-scale structured and unstructured datasets.

• Experience with GPU computing is a plus.

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization. This could be through technical leadership with ownership over a research agenda, or developing a team as a personnel manager in a new area at a larger company.

• Expert-level experience with a wide range of quantitative methods that can be applied to business problems.

• Evidence you’ve successfully been able to scope, deliver and sell your own research in a way that shifts the agenda of a large organization.

• Excellent written and verbal communication skills on quantitative topics for a variety of audiences: product managers, designers, engineers, and business leaders.

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

Qualifications

• Professional experience as a data science leader, setting the vision for how to most effectively use data in your organization

• Expert-level experience with machine learning that can be applied to business problems

• Evidence you’ve successfully been able to scope, deliver and sell your own work in a way that shifts the agenda of a large organization

• Fluent in data fundamentals: SQL, data manipulation using a procedural language, statistics, experimentation, and modeling

• Degree in a field that has very applicable use of data science / statistics techniques (e.g. statistics, applied math, computer science, OR a science field with direct statistics application)

• 5+ years of industry experience in data science and machine learning, preferably at a software product company

• 3+ years of experience managing data science teams, incl. managing/grooming managers beneath you

• 3+ years of experience partnering with executive staff on data topics

WyngCommerce is building state of the art AI software for the Global Consumer Brands & Retailers to enable best-in-class customer experiences. Our vision is to democratise machine learning algorithms for our customers and help them realise dramatic improvements in speed, cost and flexibility. Backed by a clutch of prominent angel investors & having some of the category leaders in the retail industry as clients, we are looking to hire for our data science team. The data science team at WyngCommerce is on a mission to challenge the norms and re-imagine how retail business should be run across the world. As a Senior Data Scientist in the team, you will be driving and owning the thought leadership and impact on one of our core data science problems. You will work collaboratively with the founders, clients and engineering team to formulate complex problems, run Exploratory Data Analysis and test hypotheses, implement ML-based solutions and fine tune them with more data. This is a high impact role with goals that directly impact our business. Your Role & Responsibilities - - Lead and Own the Thought Process on one or more of our core Data Science problems e.g. Product Clustering, Intertemporal Optimization, etc. - Actively participate and challenge assumptions in translating ambiguous business problems into one or more ML/optimization problems - Implement data-driven solutions based on advanced ML and optimization algorithms to address business problems - Research, experiment, and innovate ML/statistical approaches in various application areas of interest and contribute to IP - Partner with engineering teams to build scalable, efficient, automated ML-based pipelines (training/evaluation/monitoring) - Deploy, maintain, and debug ML/decision models in production environment - Analyze and assess data to ensure high data quality and correctness of downstream processes - Define and own metrics on solution quality, data quality and stability of ML pipelines - Communicate results to stakeholders and present data/insights to participate in and drive decision making Desired Skills & Experiences - - Bachelors or Masters in a quantitative field from a top tier college. - Minimum of 3+ years experience in a data science role in a technology company - Solid mathematical background (especially in linear algebra, probability theory, optimization theory, decision theory, operations research) - Familiarity with theoretical aspects of common ML techniques (generalized linear models, ensembles, SVMs, clustering algos, graphical models, etc.), statistical tests/metrics, experiment design, and evaluation methodologies - Solid foundation in data structures, algorithms, and programming language theory - Demonstrable track record of dealing with ambiguity, prioritizing needs, bias for iterative learning, and delivering results in a dynamic environment with minimal guidance - Hands-on experience in at least one of the focus areas of WyngCommerce Data Science team: (a) Product Clustering, (b) Demand Forecasting, (c) Intertemporal Optimization, (d) Reinforcement Learning, (e) Transfer Learning - Good programming skills (fluent in Java/Python/SQL) with experience of using common ML toolkits (e.g., sklearn, tensor flow, keras, nltk) to build models for real world problems - Computational thinking and familiarity with practical application requirements (e.g., latency, memory, processing time) - Experience using Cloud-based ML platforms (e.g., AWS Sagemaker, Azure ML), Cloud-based data storage, and deploying ML models in product environment in collaboration with engineering teams - Excellent written and verbal communication skills for both technical and non-technical audiences - (Plus Point) Experience of applying ML / other techniques in the domain of supply chain - and particularly in retail - for inventory optimization, demand forecasting, assortment planning, and other such problems - (Nice to have) Research experience and publications in top ML/Data science conferences

Location: Gurgaon Role: • The person will be part of data science team. This person will be working on a close basis with the business analysts and the technology team to deliver the Data Science portion of the project and product. • Data Science contribution to a project can range between 30% to 80%. • Day to Day activities will include data exploration to solve a specific problem, researching of methods to be applied as solution, setting up ML process to be applied in context of a specific engagement/ requirement, contributing to building a DS platform, coding the solution, interacting with client on explanations, integration the DS solution with the technology solution, data cleaning and structuring etc. • Nature of work will depend on stage of a specific engagement, available engagements and individual skill At least 2-6 years of experience in: • Machine Learning (including deep learning methods): Algorithm design, analysis and development and performance improvement o Strong understanding of statistical and predictive modeling concepts, machine-learning approaches, clustering, classification, regression techniques, and recommendation (collaborative filtering) algorithms o Time Series Analysis o Optimization techniques and work experience with solvers for MILP and global optimization. • Data Science o Good experience in exploratory data analysis and feature design & development o Experience of applying and evaluating ML algorithms to practical predictive modeling scenarios in various verticals including (but not limited to) FMCG, Media, E-commerce and Hospitality. • Proficient with programming in Python (must have) & PySpark (good to have). Parallel ML algorithms design and development and usage for maximal performance on multi-core, distributed and/or GPU architectures. • Must be able to write a production ready code with reusable components and integration into data science platform. • Strong inclination to write structured code as per prevailing coding standards and best practices. • Ability to design a data science architecture for repeatability of solutions • Preparedness to manage whole cycle from data preparation to algorithm design to client presentation at individual level. • Comfort in working on AWS including managing data science AWS servers • Team player and good communication and interpersonal skills • Good experience in Natural Language Processing and its applications (Good to Have)

Company Profile: Thrymr Software is an outsourced product development startup. Our primary development center is in Hyderabad, India with a team of about 100+ members across various technical roles. Thrymr is also in Singapore, Hamburg (Germany) and Amsterdam (Netherlands). Thrymr works with companies to take complete ownership of building their end to end products be it web or mobile applications or advanced analytics including GIS, machine learning or computer vision. http://thrymr.net Job Location Hyderabad, Financial District Job Description: As a Data Scientist, you will evaluate and improve products. You will collaborate with a multidisciplinary team of engineers and analysts on a wide range of problems. As a Data Scientist your responsibility will be (but not limited to) Design, benchmark and tune machine-learning algorithms,Painlessly and securely manipulate large and complex relational data sets, Assemble complex machine-learning strategies, Build new predictive apps and services Responsibilities: 1. Work with large, complex datasets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct end-to-end analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations. 2. Build and prototype analysis pipelines iteratively to provide insights at scale. Develop a comprehensive understanding of Google data ​structures and metrics, advocating for changes were needed for both products development and sales activity. 3. Interact cross-functionally with a wide variety of people and teams. Work closely with engineers to identify opportunities for, design, and assess improvements to various products. 4. Make business recommendations (e.g. cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information. 5. Research and develop analysis, forecasting, and optimization methods to improve the quality of uuser-facingproducts; example application areas include ads quality, search quality, end-user behavioral modeling, and live experiments. 6. Apart from the core data science work (subjected to projects and availability), you may also be required to contribute to regular software development work such as web, backend and mobile applications development. Our Expectations 1. You should have at least B.Tech/B.Sc degree or equivalent practical experience (e.g., statistics, operations research, bioinformatics, economics, computational biology, computer science, mathematics, physics, electrical engineering, industrial engineering). 2. You should have practical experience of working experience with statistical packages (e.g., R, Python, NumPy ) ​and databases (e.g., SQL). 3. You should have experience articulating business questions and using mathematical techniques to arrive at an answer using available data​. Experience translating analysis results into business recommendations. 4. You should have strong analytical and research skills 5. You should have good academics 6. You will have to very proactive and submit your daily/weekly reports very diligently 7. You should be comfortable with working exceptionally hard as we are a startup and this is a high-performance work environment. 8. This is NOT a 9 to 5 ​kind of job, you should be able to work long hours. What you can expect 1. High-performance work culture 2. Short-term travel across the globe at very short notices 3. Accelerated learning (you will learn at least thrice as much compared to other companies in similar roles) and become a lot more technical 4. Happy go lucky team with zero politics 5. Zero tolerance for unprofessional behavior and substandard performance 6. Performance-based appraisals that can happen anytime with considerable hikes compared to single-digit annual hikes as the market standard