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Hello!
I have over 15 years of programming experience, and graduated with a first-class degree in computer science from a well-known university in the UK.
I have worked in several sectors, including as a backend / data engineer for a large online retailer, as a full-stack developer of web and mobile apps, and as a video game developer.
I currently provide freelance software development and consulting services to startups, helping them to get their ideas off the ground, and to build a solid technical foundation for their business.
I also love teaching and mentoring, and have worked with several up-and-coming engineers to help them along their path in the industry, as well as producing educational / instructional content.
Whether you're an entrepreneur with plans to build something great, or a student hoping to kick-start their career, I look forward to working with you!
I have a PhD in Computer Science and I have extensive experience in scientific computing. I have deep expertise in C & Matlab, and I am also very proficient with PHP, MySQL, Linux, Apache, Excel, and so on. I have completed many projects involving computational modelling, statistical analysis, experimental data analysis, and innovative algorithm design & implementation.
I drive revenue. All other metrics pale in comparison.
Be it billion dollar brands or startups, I've spent the last two decades architecting technology solutions and innovative search marketing strategies (domestic & international) for e-commerce. I believe in the power of 'what if?'; leveraging hybrid expertise in search engine optimization (SEO), web development, e-commerce, and digital strategy to achieve extraordinary results.
My core competencies include search engine optimization (SEO), search marketing strategy, data wrangling (NLP/computational ontologies), and e-commerce marketing automation.
As founder and CTO of MarketKarma, I oversee organic search strategy for all enterprise accounts and work to create innovative solutions to assist retailers in tackling their online marketing challenges.
I work with brands like..
Ace Cash Express, Athleta, Banana Republic, Blackhawk Network, Blockbuster, Buckle, CheapCaribbean, CheckPast, DashFly, Diesel, DistroMex, Ebates, Eddie Bauer, Fossil, GUESS, Gap, GiftCardMall, Gold's Gym, Horchow, JCPenney, Livingston Lures, Marciano, Mavis Tire, Mavor Lane, Old Navy, Orbitz, Oriental Trading Company, PacSun, Piperlime, Red Envelope, Ritter Dental, SPFM LP, Sacha Cosmetics, ShearComfort, Smart Bargains, Swanson Health, Williams-Sonoma
Connect with me @:
Email: joey@marketkarma.com
Call: (888) 277-0225
Web: https://www.marketkarma.com
Social: https://joeyburzynski.dev
Connect: https://calendarhero.to/JoeyBurzynski
AngelList: https://angel.co/u/joeyburzynski
CoderRank: https://profile.codersrank.io/user/joeyburzynski
CodePen: https://codepen.io/JoeyBurzynski
Quora: https://www.quora.com/profile/Joey-Burzynski
Quora Spaces: https://optimization.quora.com/
LinkedIn: https://www.linkedin.com/in/miamibeachseo/
Fast Company: https://board.fastcompany.com/profile/Joey-Burzynski-Founder-CTO-MarketKarma/12629614-d0b7-4a8c-8076-5be2166473a0
Forbes: https://profiles.forbes.com/members/tech/profile/Joey-Burzynski-Founder-CTO-MarketKarma/72b6886c-bd96-4988-ad8b-14287a291009
GitHub: https://github.com/JoeyBurzynski
Gist: https://gist.github.com/JoeyBurzynski
Google: https://g.dev/EcommerceSEOExpert
LinkTree: https://linktr.ee/joeyburzynski
Medium: https://medium.com/@joeyburzynski
ORCID: https://orcid.org/0000-0002-7448-8294
StackOverflow: https://stackoverflow.com/users/3767344/joeyburzynski
Twitter: https://twitter.com/JoeyBurzynski
I build software solutions for aerospace and robotics industry ranging from building high fidelity dynamics engine software for mars and lunar landing, docking of satellites to deployment of robotic manipulators in space to building software tools for cyber physical systems ranging from rovers, leg-based robots to aerial vehicles e.g. coaxial helicopters and drones with experience in both low level and high level design.
I am also a mentor and I love programming and I love teaching especially programming with C/C++ and Python, Design patterns, Data structures and Algorithms. I love taking on new problems and help solving the problems through systematic approach which is scalable in nature. Through mentoring, I get the opportunity to accelerate my own learning curve by constantly challenging my self with problems from different domains and keep myself up to date with current trends in software design. I believe the best way I can contribute to a better society by sharing my knowledge to others and hope they can build upon that.
I always find programming to be much more than learning syntax of a language, its more of an art. Give me an opportunity and I will teach you the art of producing high quality functional codes
# **SHORT BIO**
I turn data into cash 💰
Discerning business maverick with 13 years experience leading and building data science products, statistical models, and machine learning algorithms. Motivated, thought-provoking leader with a strong entrepreneurial spirit and an astute sense of brand efficacy. Several years of experience in hiring and managing teams and building data science and analytics operations from the ground up by deploying models and data products as integral, value-added necessities to the day-to-day business operations.
# **SKILLS OVERVIEW:**
**Programming Languages** - R, Python, SQL, SAS, Julia
**Cloud** - Microsoft Azure, Google Cloud Platform
**Software** - Databricks, Azure Machine Learning, Alteryx, Google Cloud AI, Google Analytics, Twilio Segment CDP
**Machine Learning** - Regression Analysis, A/B Testing, Time Series Forecasting, Cluster Analysis, Principal Components, Random Forests, Gradient Boosting, XGBoost, GLM, H2O AI, Product Recommenders, AutoML
**Databases** - Azure SQL, Microsoft SQL Server, Google Big Query, AWS MySQL, PostgreSQL
**Visualization** - Excel, PowerBI, MicroStrategy, Tableau, Mode Analytics
**Web Frameworks** - Shiny, HTML, CSS, JavaScript, APIs
**Project Management** - Jira, Workfront, Agile, Kanban, Six Sigma, Confluence, Microsoft Teams, Slack, Miro
# **CONFERENCE AND EVENT TALKS:**
**Data Science Salon - Miami, FL - Feb 8-9, 2018:** https://www.youtube.com/watch?v=6W24QQx72JI
**Data Science Salon – Dallas, TX – Apr 27, 2018:** https://www.youtube.com/watch?v=YV8brwe-bWA
**South Florida Interactive Marketing Association – Miami, FL – Jul 18, 2019:** https://sfima.com/event/customer-personalization-using-ai-the-easy-way/
**Miami Python Meetup Group – Royal Caribbean HQs, Miami, FL – Aug 15, 2019:** https://www.meetup.com/python-miami/events/263777763/
**Marketing Analytics and Data Science Conference West – San Francisco, CA – July 28-30, 2020:** https://informaconnect.com/marketing-analytics-and-data-science-west/speakers/
# **DATA SCIENCE AND AI ARTICLES:**
**Automated Time Series Forecasting in R –** https://www.remixinstitute.com/blog/automate-your-kpi-forecasts-with-only-1-line-of-r-code-using-autots/
**Business AI for Small-to-Medium Sized Businesses -** https://www.remixinstitute.com/blog/business-ai-for-small-to-medium-sized-businesses-with-remixautoml
I have over 7 years experience in data science/analytics. I have delivered value to more than 120 clients in the past, and built KPIs for business measures. I am passionate about solving problems with statistics.
See the power of our Data Modelling tutors through glowing user reviews that showcase their successful Data Modelling learning journeys. Don't miss out on top-notch Data Modelling training.
“Girish was excellent to work with. He is very patient and understanding, which is so important for someone like myself who is very new to this field. He took the time to understand where I was coming from and what I needed to accomplish. I will definitely continue to use Girish for all of my future web3 needs. Highly recommended. AAA+++“
Skajosborn / Dec 2024
Girish Ramnani
Data Modelling tutor
“David was knowledge and help me understand the concept I was stuck on. He help me get a better understanding of the small aspects I was have trouble such as where data was being sent and how it was being received in my assignment. He was patient, and allowed me to think through the problems and ask questions where I was getting stuck.“
Tanner Galloway / Dec 2024
David Y. Stephenson
Data Modelling tutor
“James took the time to look at my Power Automate flow and work out what the issue was with the specific phrasing that was stopping it from working.
Not only am I really pleased with the results of our troubleshooting sessions, but he was a joy to talk to and was patient with me throughout.“
QualityChimp / Dec 2024
James D. Bartlett III
Data Modelling tutor
“Today was the first time meeting Bilal. It was more an introductory session to get to know each other than a mentoring session. He was very polite throughout the whole session and was not pushy at all with trying to sell himself or his services. I'm still considering who to take as a mentor, but he is definitely in consideration. Thank you for chatting with me today!“
Andrew Huntington / Dec 2024
BilalurRehman
Data Modelling tutor
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Frequently asked questions
How to learn Data Modelling?
Learning Data Modelling effectively takes a structured approach, whether you're starting as a beginner or aiming to improve your existing skills. Here are key steps to guide you through the learning process:
Understand the basics: Start with the fundamentals of Data Modelling. You can find free courses and tutorials online that cater specifically to beginners. These resources make it easy for you to grasp the core concepts and basic syntax of Data Modelling, laying a solid foundation for further growth.
Practice regularly: Hands-on practice is crucial. Work on small projects or coding exercises that challenge you to apply what you've learned. This practical experience strengthens your knowledge and builds your coding skills.
Seek expert guidance: Connect with experienced Data Modelling tutors on Codementor for one-on-one mentorship. Our mentors offer personalized support, helping you troubleshoot problems, review your code, and navigate more complex topics as your skills develop.
Join online communities: Engage with other learners and professionals in Data Modelling through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Data Modelling skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Data Modelling in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Data Modelling is continually evolving, staying informed about the latest developments and advanced features is essential. Follow relevant blogs, subscribe to newsletters, and participate in workshops to keep your skills up-to-date and relevant.
How long does it take to learn Data Modelling?
The time it takes to learn Data Modelling depends greatly on several factors, including your prior experience, the complexity of the language or tech stack, and how much time you dedicate to learning. Here’s a general framework to help you set realistic expectations:
Beginner level: If you are starting from scratch, getting comfortable with the basics of Data Modelling typically takes about 3 to 6 months. During this period, you'll learn the fundamental concepts and begin applying them in simple projects.
Intermediate level: Advancing to an intermediate level can take an additional 6 to 12 months. At this stage, you should be working on more complex projects and deepening your understanding of Data Modelling’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Data Modelling generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Data Modelling, contributing to major projects, and possibly specializing in specific areas within Data Modelling.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Data Modelling. Engaging with new developments, tools, and methodologies in Data Modelling is a continuous process throughout your career.
Setting personal learning goals and maintaining a regular learning schedule are crucial. Consider leveraging resources like Codementor to access personalized mentorship and expert guidance, which can accelerate your learning process and help you tackle specific challenges more efficiently.
How much does it cost to find a Data Modelling tutor on Codementor?
The cost of finding a Data Modelling tutor on Codementor depends on several factors, including the tutor's experience level, the complexity of the topic, and the length of the mentoring session. Here is a breakdown to help you understand the pricing structure:
Tutor experience: Tutors with extensive experience or high demand skills in Data Modelling typically charge higher rates. Conversely, emerging professionals might offer more affordable pricing.
Pro plans: Codementor also offers subscription plans that provide full access to all mentors and include features like automated mentor matching, which can be a cost-effective option for regular, ongoing support.
Project-based pricing: If you have a specific project, mentors may offer a flat rate for the complete task instead of an hourly charge. This range can vary widely depending on the project's scope and complexity.
To find the best rate, browse through our Data Modelling tutors’ profiles on Codementor, where you can view their rates and read reviews from other learners. This will help you choose a tutor who fits your budget and learning needs.
What are the benefits of learning Data Modelling with a dedicated tutor?
Learning Data Modelling with a dedicated tutor from Codementor offers several significant benefits that can accelerate your understanding and proficiency:
Personalized learning: A dedicated tutor adapts the learning experience to your specific needs, skills, and goals. This personalization ensures that you are not just learning Data Modelling, but exceling in a way that directly aligns with your objectives.
Immediate feedback and assistance: Unlike self-paced online courses, a dedicated tutor provides instant feedback on your code, concepts, and practices. This immediate response helps eliminate misunderstandings and sharpens your skills in real-time, making the learning process more efficient.
Motivation and accountability: Regular sessions with a tutor keep you motivated and accountable. Learning Data Modelling can be challenging, and having a dedicated mentor ensures you stay on track and continue making progress towards your learning goals.
Access to expert insights: Dedicated tutors often bring years of experience and industry knowledge. They can provide insights into best practices, current trends, and professional advice that are invaluable for both learning and career development.
Career guidance: Tutors can also offer guidance on how to apply Data Modelling in professional settings, assist in building a relevant portfolio, and advise on career opportunities, which is particularly beneficial if you plan to transition into a new role or industry.
By leveraging these benefits, you can significantly improve your competency in Data Modelling in a structured, supportive, and effective environment.
How does personalized Data Modelling mentoring differ from traditional classroom learning?
Personalized Data Modelling mentoring through Codementor offers a unique and effective learning approach compared to traditional classroom learning, particularly in these key aspects:
Customized content: Personalized mentoring adapts the learning material and pace specifically to your needs and skill level. This means the sessions can focus on areas where you need the most help or interest, unlike classroom settings which follow a fixed curriculum for all students.
One-on-one attention: With personalized mentoring, you receive the undivided attention of the tutor. This allows for immediate feedback and detailed explanations, ensuring that no questions are left unanswered, and concepts are fully understood.
Flexible scheduling: Personalized mentoring is arranged around your schedule, providing the flexibility to learn at times that are most convenient for you. This is often not possible in traditional classroom settings, which operate on a fixed schedule.
Pace of learning: In personalized mentoring, the pace can be adjusted according to how quickly or slowly you grasp new concepts. This custom pacing can significantly enhance the learning experience, as opposed to a classroom environment where the pace is set and may not align with every student’s learning speed.
Practical, hands-on learning: Mentors can provide more practical, hands-on learning experiences tailored to real-world applications. This direct application of skills is often more limited in classroom settings due to the general nature of the curriculum and the number of students involved.
Personalized mentoring thus provides a more tailored, flexible, and intensive learning experience, making it ideal for those who seek a focused and practical approach to mastering Data Modelling.