Top Senior Data science in python Developers - Sep 2017

Natural Language Processing Engineer

Machine Learning / Natural Language Processing engineer, Pythonista, husband, proud father. Working as a Machine Learning Engineer at LogMeIn structuring noisy textual data.

Data science and research-centric software maker

When I first learned how to program, it was a exhilarating; it felt like discovering fire. A couple of months later I made a program that played the boardgame Clue and asked my family really nicely (I think) to play against it. Even though it lost, I was hooked. It's this project-centric approach that can still motivate me to learn new tools, or stay up late coding. Building things is fun. And I've always tried to follow my interests towards projects and tools that excite me. I spent time making computational models in several summer internships helped design and build a serious game that simulated molecular biology. I like sharing what I'm interested in, so teaching programming and tools comes naturally. I mentor courses in data science and Python and love talking shop.

Data science practitioner | Machine Learning Engineer | Open Source developer

Availability: I am usually available between 5:00-9:00 UTC for a chat or live session on weekdays. I can make time more freely during weekends for the same. As for offline helps, I can do them on my own time once I get the details of the task. Data Scientist, Engineer and Machine Learning practitioner on a quest to build intelligent products and understand intelligence better while at it. I have worked on online courses and taken various workshops because of my inclination towards mentoring and helping others understand things better. My author profile with my current publisher: Past: 2x GSoCer, Data Engineer @ RedCarpetUp (YC and Google Launchpad startup) Current: Data Engineer @ SocialCops, GSoC mentor, Technical Author @ Packt Publishing, Freelancer

Python, Machine Learning, Data Engineering

I use mathematics and machine learning to analyze & explain data. When the machine doesn't learn, I do it the old-fashioned way: I use my brain and do my own learning instead. I've been working as a software engineer for the last 5-6 years. I consider my skillset to lie somewhere in the intersection between software engineering , data engineering and data science (machine learning) (that is to say, in other words front-end is not my thing). I've worked with all the cool Python libraries through the whole "data lifecycle": crawling data, queuing systems, db management, training ML models, API design and deployment management (Ansible mainly) Libraries include: Pandas, NumPy, Scikit-learn, matplotlib, Flask, python-rq, celery, requests (of course), selenium and many more. I do consider myself to a major extent a data engineer as well. I've managed mainly Hadoop clusters, MongoDB and ElasticSearch ones. Occasionally I teach corporate seminars on such topics. I'm also a huge fun of Redis and I always try to fit it in my architecture if I think it can help (it almost always can). I've also research experience on such topics and a couple of publications as well. You may have a look here and I have consulted many international companies in the areas of predictive analytics, market analysis and marketing budget allocation, mainly in the telecoms and retail industry. Occasionally, I also teach corporate courses & seminars on software engineering, data analysis and big data systems engineering.

Data Scientist | Data Visualization | Columbia Graduate Student | Computer Science Engineer | IIIT-H Alumnus

I am currently a graduate student at Columbia University majoring in Data Science, with an interest in Statistical Inference and Modeling, Data Visualization as well as Machine Learning. In particular, I have strong quantitative skills from my mathematics background and experience with data mining and analysis through Python, MATLAB. I also enjoy working on web and mobile development and learning the latest tools and technologies. At Columbia, I am learning the skills with undivided Focus and Consistency, giving proper Significance to learning and being Restorative towards the issues faced along the way, trying always to be deliberative towards my career goals. Deliberative, Significance, Consistency, Restorative, Focus - These aren’t just words for me, these are my superpowers. My learning experiences, marathon adventures and quantified self enthusiasm are perfectly captured by them.

Chief Technology Officer

Embedded Systems and VLSI Designs Combat Systems Integration C4ISR and Comat Management Systems (CMS) Net-Centric Warfare Digital Signal Processing with soecialisation in underwater signal procesing Data Science and Internet of Things (IoT) Predicitve Business Analytics Specialties: Research and Development of Military Systems Project Management

Data Science/Software Consultant - Computer Science Professor at Fordham University/Courant Institute

8+ years of experience in Software Development; currently architect, lead and manage technical teams building Data Analytic Engine on high-performance and scalable distributed platform; apply Machine Learning algorithms to develop predictive systems; collaborate with high-level executives and achieve highly on creating Business Model & Strategies for Analytic Engine; successfully managed Software Development teams for high quality large scale products (best software product awards in 2008); ); pioneered in the area of “Stochastic Ruin Algorithm for Machine Learning (Congressus Numerantium 2015)”

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