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Nata L, Data Analyst with BI and Data Engineering skills (Senior Certified Tableau Engineer)

Germany
Last Updated: 23 Apr 2024
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- Oriented Data and Business Intelligence Analysis engineer with Data Engineering skills. - 6+ years of experience with Tableau - Experience in Operations analysis, building charts & dashboards - 20+ years of experience in data mining, data analysis, and data processing. Unifying data from many sources to create interactive, immersive dashboards and reports that provide actionable insights and drive business results. - Adept with different SDLC methodologies - Waterfall, Agile SCRUM - Knowledge of performing data analysis, data modeling, data mapping, batch data processing, and capable of generating reports using reporting tools such as Power BI (advanced), Sisence(Periscope) (expert), Tableau (Advanced), Data Studio (Advanced) - Experience in writing SQL Queries, Big Query, Python, R, DAX to extract data and perform Data Analysis - AWS, Redshift - Combined expertise in data analysis with solid technical qualifications. - Advanced English, Intermediate German - Location: Germany

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Random Forest

Random Forest

Python

Python   6 yr.

SQL

SQL   8 yr.

Microsoft Power BI

Microsoft Power BI

Data Analysis Expressions (DAX)

Data Analysis Expressions (DAX)   4 yr.

Tableau

Tableau   6 yr.

View Nata

Nadya, Data Analyst, Economic Processes Analysis & Modelling

Ukraine
Last Updated: 23 Apr 2024

- 10+ years in Forecasting, Analytics & Math Modelling - 8 years in Business Analytics and Economic Processes Modelling - 5 years in Financial Forecasting Systems - 5 years in Data Science - 3 years in Web Development - Master of Statistics and Probability Theory (diploma with honours), PhD (ABD) - BSc in Finance - Strong knowledge of Math & Statistics - Strong knowledge of R, Python, VBA - Strong knowledge of PostgreSQL and MS SQL Server - Knowledge of C# - Knowledge of .net web development technologies - Basic web technologies (JavaScript) - Self-motivated, conscientious, accountable, addicted to data processing, analysis & forecasting

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Random Forest

Random Forest

Data Analysis

Data Analysis   10 yr.

Python

Python

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Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Manager
Maria Lapko
Global Partnership Manager

Only 3 Steps to Hire Random Forest Engineers

1
Talk to Our Talent Expert
Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
2
Meet Carefully Matched Talents
Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person.
3
Validate Your Choice
Bring new talent on board with a trial period to confirm you hire the right one. There are no termination fees or hidden costs.

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Henry Akwerigbe
This is a super team to work with. Through Upstaff, I have had multiple projects to work on. Work culture has been awesome, teammates have been super nice and collaborative, with a very professional management. There's always a project for you if you're into tech such Front-end, Back-end, Mobile Development, Fullstack, Data Analytics, QA, Machine Learning / AI, Web3, Gaming and lots more. It gets even better because many projects even allow full remote from anywhere! Nice job to the Upstaff Team 🙌🏽.
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I have been working with Upstaff for over a year on a project related to landscape design and management of contractors in land design projects. During the project, we have done a lot of work on migrating the project to a multitenant architecture and are currently working on new features from the backlog. When we started this project, the hiring processes were organized well. Everything went smoothly, and we were able to start working quickly. Payments always come on time, and there is always support from managers. All issues are resolved quickly. Overall, I am very happy with my experience working with Upstaff, and I recommend them to anyone looking for a new project. They are a reliable company that provides great projects and conditions. I highly recommend them to anyone looking for a partner for their next project.
Владислав «Sheepbar» Баранов
Владислав «Sheepbar» Баранов
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Yanina Antipova
Yanina Antipova
Хочу виразити велику подяку за таку швидку роботу по підбору двох розробників. Та ще й у такий короткий термін-2 дні. Це мене здивувало, адже ми шукали вже цілий місяць. І знайдені кандидати нам не підходили Це щось неймовірне. Доречі, ці кандидати працюють у нас і зараз. Та надать приклад іншим працівникам. Гарного дня!)
Наталья Кравцова
Наталья Кравцова
I discovered an exciting and well-paying project on Upstaff, and I couldn't be happier with my experience. Upstaff's platform is a gem for freelancers like me. It not only connects you with intriguing projects but also ensures fair compensation and a seamless work environment. If you're a programmer seeking quality opportunities, I highly recommend Upstaff.
Volodymyr
Volodymyr
Leaving a review to express how delighted I am to have found such a great side gig here. The project is intriguing, and I'm really enjoying the team dynamics. I'm also quite satisfied with the compensation aspect. It's crucial to feel valued for the work you put in. Overall, I'm grateful for the opportunity to contribute to this project and share my expertise. I'm thrilled to give a shoutout and recommendation to anyone seeking an engaging and rewarding work opportunity.

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FAQs about Random Forest Development

How do I hire a Random Forest developer? Arrow

Are you desperately looking for a Random Forest developer validated to your requirements and skills? Are you lacking in resources and tools to find the right developer? If yes, then you are at the right place! Because at Upstaff, the selection of the Random Forest Developer is done professionally as per your requirement, in a short time of just a few days, from calling to the instant task of your validated developer, with all your required skills.

Where is the best place to find Random Forest developers? Arrow

Sure enough, within the network there must be dozens, if not hundreds, of services and platforms where you can look for the Random Forest guy you need, but just Upstaff lets you sort out the best of the best real qualified developers practically in a couple of minutes, so that you will be able to select the one whose personality will be a perfect fit to your company. This is the case when you can create a genuinely “Pizza” type of service in the field of custom software development.

How are Upstaff Random Forest developers different? Arrow

Vetting by expert human reviewers is combined with historically curated feedback from clients and team-mates, which has enabled us to save, on average, more than 50 hours for each client team evaluating Random Forest candidates for every position. We live and breathe technical excellence, borne out of extensive industry expertise.

How quickly can I hire Random Forest developers through Upstaff? Arrow

Our process begins with a 30-minute discovery call: we’ll discuss your pain points, technical requirements, and team diversity. Meet Carefully Matched Random Forest Talents. Upon your meeting confirmation, we’ll send you profiles and arrange an introduction call with the right talents for your project, within 1-3 days. Schedule a call to meet Random Forest engineers in person. Make the right call. Bring a new Random Forest developer on board with a trial period: confirm that the person you hired does the job right, no termination fees and no hidden fees.

How does Upstaff vet remote Random Forest engineers? Arrow

After this introductory round, Upstaff Managers do an eval of the soft skills of the candidates before the hiring decision is approved or rejected. For the hard skills, the Upstaff Staffing Platform has a short testing session to check their Random Forest skills or engage a senior developer to do a technical interview for more senior developers. You can reuse some of the hard and soft skills of past candidates to connect them with other jobs in the future (see below). Upstaff managers also do an eval of the talent before approving them for further work, allowing us to accelerate the work and ability to scale, but also providing information to clients on the talent pipeline. Finally, we also have a matching engine within the work mining system that matches candidates and jobs in real time.

How to hire Random Forest developer? Arrow

If recruiting services and job boards are not your 1st option, you may want to consider a client-oriented service like Upstaff to find & hire Random Forest developers. Upstaff has a network of vetted and tested Random Forest developers. Here, you can hire web developers for a few simple coding tasks with Random Forest.

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Table of Contents

How and where is Random Forest used?

  • Customer Churn Prediction: Identify customers likely to leave a service
  • Fraud Detection: Detect fraudulent activities in financial transactions
  • Medical Diagnosis: Assist in diagnosing diseases based on symptoms
  • Sentiment Analysis: Analyze and classify opinions in social media posts
  • Recommendation Systems: Provide personalized recommendations to users
  • Image Classification: Classify objects or scenes in images accurately
  • Stock Market Prediction: Forecast stock prices and trends
  • Credit Scoring: Assess creditworthiness of individuals applying for loans
  • Anomaly Detection: Identify outliers or unusual patterns in data
  • Remote Sensing: Interpret satellite images for various applications

Compare Junior, Middle, Senior, and Expert/Team Lead Random Forest Developer roles

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior0-2 years
  • Assist in data preprocessing
  • Implement basic Random Forest models
  • Participate in code reviews
$60,000
Middle2-5 years
  • Optimize Random Forest algorithms
  • Provide technical guidance to juniors
  • Contribute to model evaluation
$80,000
Senior5-8 years
  • Lead complex model development projects
  • Mentor team members
  • Collaborate with stakeholders
$100,000
Expert/Team Lead8+ years
  • Define Random Forest strategies
  • Manage project timelines
  • Drive innovation in ML processes
$120,000

Quick Facts about Random Forest.

  • Random Forest technology was created in 2001.
  • The most popular project types using this technology are predictive modeling and data mining.
  • The technology entry threshold is relatively low compared to other advanced machine learning techniques.
  • One of the most popular related technologies to Random Forest is Gradient Boosting.
  • A fun fact about Random Forest is that it gets its name from the idea of creating an ensemble of decision trees, each “voting” on the outcome.

TOP Random Forest Related Technologies

  1. Python (Guido van Rossum, 1991)
  2. R (Ross Ihaka and Robert Gentleman, 1995)
  3. Weka (University of Waikato, 1993)
  4. TensorFlow (Google Brain Team, 2015)
  5. scikit-learn (David Cournapeau, 2007)

What are top Random Forest instruments and tools?

  • RandomForestSRC: A tool by the company ‘randomForestSRC’ that was released in 2013
  • Scikit-learn: A tool by the company ‘Scikit-learn’ that was released in 2007
  • WEKA: A tool by the company ‘WEKA’ that was released in 1993

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Talk to Our Talent Expert

Our journey starts with a 30-min discovery call to explore your project challenges, technical needs and team diversity.
Manager
Maria Lapko
Global Partnership Manager