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A Data Scientist with a background in mathematics and statistics and experience in NLP, Image Processing, engineering data in datasets, and machine learning methods such as Bayesian Machine Learning, Neural Networks, and other algorithms such as Random Kitchen Sink, Regression/Random Forests, and Generalised Linear Models.
PhD and MSc qualified results driven data scientist/statistician with proven expertise in the application of statistical modeling/machine learning. Strong knowledge of predictive modeling techniques with the ability to generate actionable insight from complex data and stakeholder requirements. Recently awarded an MSc. in Data Science & Analytics from Royal Holloway, Univ. London with distinction.
• 12+ years experience in deriving pragmatic, actionable insight from data, • Advanced analytics, Predictive modelling, Data Visualisation, • Process Automation, Machine Learning, • Locating bottlenecks and optimising business operations, • Strong background in the engineering research and development, • Data lifecycle management (ETL) • Product Optimisation, Design of Experiment using Simulation Tools https://www.linkedin.com/in/kprzysowa/
I have 18 years experience working in Research and Development, of which the last 8 have been spent working as a data scientist. I undertake projects in Natural Language Processing and other areas of Machine Learning and Artificial Intelligence for clients ranging from startups to multinationals. My work enables my clients to innovate.
• Cornell Honours graduate in Statistical Sciences with applied project/team experience in statistical consulting units and hospitality industry • Background in theoretical statistics and applied mathematics with advanced set of programming skills; project management experience handling large data sets – sampling/cleaning, analysing, presenting • Business Analytics 2017 MSc student at Imperial College aiming to pursue career in data science more
I am passionate about Analytics and using statistical techniques to create a data driven organisation. I am familiar with most statistical techniques including Linear and Logistic Regression, CHAID, Clustering, Neural Networks, Association Models as well as NLP for text analysis. I can bridges the gap between the technology, statistics and business. He is also passionate about the value of Social Media data and its value in better understanding of customers.
I have architected and developed SaaS predictive solutions for marketing, experienced in working in an Agile environment and product development.
Skills: R, SQL, SPSS, Tableau
2 of the last organisations I have worked for have been in the Times Tech Track 100 (Black Swan 2017, Portal 2012)
Someone who looks at issues and problems within a business and searches masses of data to find the answers. Their field encompasses everything related to data cleansing, preparation, and analysis. Data science is an umbrella term under which many scientific methods apply.
What is the average rate for a data scientist?
The daily rate is £500-£550 depending on company size, location and candidate experience.
What are the top qualities to look for in a data scientist?
Complex problem-solving skills, strong skills in mathematics, a good understanding of coding, and the ability to assess risk.
Data scientist vs big data developer
Big Data consists of lots of items of Data. Data Science uses statistics to find the meaning hidden within the data to understand what is happening and why, whilst also making predictions about what will happen next.
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