Role: DataScientist Location: Bangalore Job description: What will you do ?? • Develop, process, cleanse and enhance data collection procedures from multiple data sources • Conduct & deliver experiments and proof of concepts to validate business ideas and potential value. • Test, troubleshoot and enhance the developed models in a distributed environments to improve it's accuracy. • Work closely with product teams to implement algorithms with R and/or Python. • Design and implement scalable predictive models, classifiers leveraging machine learning, data regression. • Facilitate integration with enterprise applications using APIs to enrich implementations. Ideal Characteristics? • 10+ years of experience in designing/developing industrial IT solutions • Minimum 3 years of experience in developing and deploying machine learning, deep learning, NLP solutions. • Experience with common data science toolkits, such as R, NumPy - Excellence in at least one of these is mandatory. • Proficiency with any one NoSQL databases such as MongoDB, Cassandra, HBase • Should have good awareness on entire machine learning/ predictive modeling & implementation process: Model design, feature planning, system infrastructure, production setup and monitoring, and release management. • Excellent understanding of machine learning techniques and algorithms, such as SVM, Decision Forests, k-NN, Naive Bayes etc. • Experience in selecting features, building and optimizing classifiers using machine learning techniques. • Prior experience with data visualization tools, such as D3.js, GGplot, etc. • Good knowledge on statistics skills, such as distributions, statistical testing, regression, etc. • Adequate presentation and communication skills to explain results and methodologies to non-technical stakeholders. Candidate Philosophy: • Proven Ability to learn and work on latest technology, have good analytical skills and pickup faster. • Should have excellent communication, interpersonal skills and be a team player. • Should have Strong Leadership skills to drive the technical aspects of the project. • Able to act as the technical change agent in the project, mentoring the lesser experienced • Experience in building strong relationship with the Onsite Counterparts
We are looking for Data Scientists who will help us build high-quality prediction and recommendation systems to be integrated with our products. Your primary focus will be to use your quantitative knowledge, programming skills and analytical ingenuity to discover information hidden in vast amounts of data, and help businesses make smarter decisions. Responsibilities: Works to develop analytical/ data mining/ machine learning models using Python, R and other tools Gather, evaluate and document requirements, ability to build an algorithm (statistical/ data mining/ machine learning) based on requirements and specifications provided Works with data and is able to conceptualize and improvise analytical solutions to problems Ability to deploy analytical algorithms within a larger business application Ability to visualize data and results of data analysis & analytical models Requirements: Experience with statistical analysis using R and Python. Experience with Spark, ML and Java as plus Good experience in data discovery, exploration and algorithm development Experience with working on large data sets and developing scalable algorithms Hands-on experience of machine learning and data mining algorithms such as decision trees, classifiers, text mining/ NLP, clustering, and regression Exp in SAS, SPSS is a plus Knowledge of Hadoop and other distributed computing platforms Broad knowledge of data mining, NLP algorithms, machine learning algorithms and other techniques technologies Strong analytical and problem-solving skills If this sounds like something you enjoy, then do apply. We'd love to hear from you!
• Hands-on experience as a Data Scientist • Through understanding of Machine Learning and Statistical models • Experience in R and Python • Experience in one or more areas of predictive modelling, text mining, time series analysis and unsupervised learning methods • Innovative thinking in building complex learning models • Identify and extract interesting pattern from structured and unstructured data. • Experience in building state of the art solutions with structured, semi structured and unstructured data. • Collaborate with a cross-functional team including data scientists, business analysts and software engineers. • Experience with machine learning frameworks e.g., Theano, KERAS,Tensorflow • Additional programming skills like Java and Scala would be a plus.
Job Responsibilities: Part of the Research team working continuously to improve ShieldSquare’s bot-human classification engine. Analyze billions of web page visits per month amounting to many terabytes of data and apply state-of-the-art Data Science and ML techniques to derive new patterns. As an area expert in ML, guide and mentor junior team members. Requirements: Excellent quantitative skills and experience in statistics and machine learning Interest in learning and applying the learnings to achieve the objectives. Interest in experimentation and data-driven improvisation Experience in leading/mentoring data scientists/ML engineers/scientists Hands-on knowledge of deep learning Any of the following qualifications are preferred: Knowledge of SQL/Visualization tools/Python: Pandas, Scipy suite Knowledge of Deep learning tools: Tensorflow/Keras/PyTorch/Caffe/Theano/Mxnet etc. Completion of online courses in Data Science/ML domain Participation in Data Science/ML competitions Contribution in open source projects Experience in solving real-world Data Science problems Experience in A/B testing, multi-armed bandits, controlled experiments, reinforcement learning What’s in it for you? Experience in working on billions of newly generated data points per month (many terabytes of data) using cutting-edge Data Science tools. Experience in R&D of real-time bot-human classification engine handling 1000s of request per second Work and learn as part of the cross-functional R&D team (some with PhD) building the industry leading bot-human classification engine Play a high impact role in a setting where data-driven improvements are pushed to production code on a daily basis
Job Responsibilities: Part of the Research team working continuously to improve ShieldSquare’s bot-human classification engine. Analyze billions of web page visits per month amounting to many terabytes of data and apply state-of-the-art Data Science/ML tools to derive new patterns. Build and own custom classification engines for novel use cases and high priority customer requirements. Lead and mentor junior team members Requirements: Experience in leading/mentoring data scientists Excellent quantitative skills and knowledge of statistics Interest in learning and applying the learnings to achieve the objectives. Interest in experimentation and data-driven improvisation Interest in building and owning prototypes of end-to-end modules for proof-of-concept Ability to work hands-on with SQL and Python Any of the following qualifications are preferred: Knowledge of SQL/Visualization tools/Python: Pandas, Scipy suite, Tensorflow, Keras Completion of online courses in Data Science/ML domain Participation in Data Science/ML competitions Contribution in open source projects Experience in solving real-world Data Science problems Knowledge of Machine Learning and Deep Learning techniques Experience in A/B testing, controlled experiments What’s in it for you? Experience in working on billions of newly generated data points per month (many terabytes of data) using cutting-edge Data Science tools. Experience in R&D of real-time bot-human classification engine handling 1000s of request per second Work and learn as part of the cross-functional R&D team (some with PhD) building the industry leading bot-human classification engine Play a high impact role in a setting where data-driven improvements are pushed to production code on a daily basis
Job Description : If you are visionary and a statistical mastermind and are keen to make a difference in a unique way, then we are looking for you…. We are looking for highly passionate and enthusiastic players for solving problems in medical data analysis using a combination of image processing, machine learning and deep learning. As a Senior Computer Scientist at SigTuple you will have the onus of creating and leveraging the state-of-the-art algorithms in machine learning, image processing and AI which will impact billions of people across the world by creating healthcare solutions that are accurate and affordable. You will collaborate with our current team of super awesome geeks in cracking super complex problems in a simple way by creating experiments, algorithms and prototypes that not only yield high-accuracy but are also designed and engineered to scale. We believe in innovation - needless to say that you will be part of creating intellectual properties like patents and contributing to the research communities by publishing papers - it is something that we value the most What we are looking for: Hands on experience along with a strong understanding of foundational algorithms in either machine learning, computer vision or deep learning. Prior experience of applying these techniques on images and videos would be good-to-have. Hands on experience in building and implementing advanced statistical analysis and machine learning and data mining algorithms. Programming experience in C, C++, Python What should you have: 3 - 5 years of relevant experience in solving problems using machine learning or computer vision Bachelor degree or Master degree or PhD in computer science or related fields. Be an innovative and creative thinker, somebody who is not afraid to try something new and inspire others to do so. Thrive in a fast-paced and fun environment. Work with a bunch of data scientist geeks and disruptors striving for a big cause. What SigTuple can offer: You will be working with an incredible team of smart & supportive people, driven by a common force to change things for the better. With an opportunity to deliver high-calibre mobile and desktop solutions integrated with hardware that will transform healthcare ground up, there will ultimately be different challenges for you to face. Sufficient to say that if you thrive in these environments, the buzz alone will keep you energized. In short you will snag a place at the table of one of the most vibrant start-ups in the industry!!
Primary Skills : - B.Tech/MS/PhD degree in Computer Science, Computer Engineering or related technical discipline with 3-4 years of industry experience in Data Science. - Proven experience of working on unstructured and textual data. Deep understanding and expertise of NLP techniques (POS tagging, NER, Semantic role labelling etc). - Experience working with some of the supervised/unsupervised learning ML models such as linear/logistic regression, clustering, support vector machines (SVM), neural networks, Random Forest, CRF, Bayesian models etc. The ideal candidate will have a wide coverage of the different methods/models, and an in depth knowledge of some. - Strong coding experience in Python, R and Apache Spark. Python Skills are mandatory. - Experience with NoSQL databases, such as MongoDB, Cassandra, HBase etc. - Experience of working with Elastic search is a plus. - Experience of working on Microsoft Azure is a plus although not mandatory. - Basic knowledge of Linux and related scripting like Bash/shell script. Role Description (Roles & Responsibilities) : - Candidate will research, design and implement state-of-the-art ML systems using predictive modelling, deep learning, natural language processing and other ML techniques to help meeting business objectives. - Candidate will work closely with the product development/Engineering team to develop solutions for complex business problems or product features. - Handle Big Data scale for training and deploying ML/NLP based business modules/chatbots.
Sigmoid is a fast growing Product Based BIG DATA startup. Sequoia Funded & Backed by experienced Professionals & Advisors. Sigmoid is revolutionizing business intelligence and analytics by providing unified tools for historical and real time analysis on Apache Spark. With their suite of products, Sigmoid is democratizing streaming use-cases like RTB Data Analytics, Log Analytics, Fraud Detection, Sensor Data Analytics etc. Sigmoid can enable the customers’ engineering team to set up their infrastructure on Spark and ramp up their development timelines, or enable the analytics team to derive insights from their data. Sigmoid has created a real time exploratory analytics tool using on Apache SPARK which not only vastly improves performance but also reduces the cost. A user can quickly analyse huge volumes of data, filter through multiple dimensions, compare results across time periods and carry out root cause analysis in a matter of seconds. Leading organisations across industry verticals are currently using Sigmoid’s platform in production to create success stories. Education Qualification: -BTech Graduates from Top Tier Colleges (IITs,NITs,IIITs,BITs, etc) with good CGPAs. -Strong experience working on Algorithms, R, Excel, SQL & Python. -Significant experience building and interpreting Machine Learning models on real business data, e.g. logistic regression, naïve Bayes, Random Forests, Boosted trees. -Strong understanding of and experience applying statistical techniques, e.g. regularization, hypothesis testing, analytical and empirical confidence intervals, bootstrap sampling. -Experience designing and conducting controlled experiments, performing statistical analysis of collected data, and presenting results to other stakeholders. -Experience on Deep Learning & Neural Networks is highly preferred. Production Level ML experience is preferred. Core Skills: -Excellent analytical and problem-solving skills, including the ability to identify root causes and recommend solutions. -Identifies data sources, integrates multiple sources or types of data, and applies expertise within a data source in order to develop methods to compensate for limitations and extend the applicability of the data. -Applies (or develops if necessary) tools and pipelines to efficiently collect, clean, and prepare massive volumes of data for analysis. -Transforms formulated problems into implementation plans for experiments by applying (and creating when necessary) the appropriate methods, algorithms, and tools, and statistically validating the results against biases and errors. -Interprets results and develops insights into formulated problems within the business/customer context and provides guidance on risks and limitations. -Acquires and uses broad knowledge of innovative methods, algorithms, and tools from within Microsoft and from the scientific literature, and applies his or her own analysis of scalability and applicability to the formulated problem. -Validates, monitors, and drives continuous improvement to methods, and proposes enhancements to data sources that improve usability and results. Salary is not a constraint for the right talent.
• Identifying and modeling the key drivers of consumer behavior using internal and external data. • Developing prediction models to deliver key business outcomes. • Problems include working on demand forecasting, demand driven supply planning etc. • Developing optimized transportation network design for Shuttl operations to drive strategic growth • Developing algorithms to predict static and dynamic schedule of Shuttl arrival times. • Presenting clear and actionable recommendations to Products and Engineering leadership. • Relentless pursuit of achieving business goals using the power of data
1. Product: - Identify important questions with the product team and answer them with data - Create a culture of measurement and metrics across the company by developing key success metrics for the product - Work with company leaders to understand product roadmap and influence/improve it using quantitative research - Be our source of bitter truth against all product assumptions 2. Sales: - Work with sales team to automate internal dashboards which help company leaders make strategic decisions - Develop reports/research based on our data that help reduce sales time - Work with our product team to build and maintain integrations with other business systems