Remote Data Scientist Jobs

Remote data scientist jobs at U.S. companies in 2021

We, at Turing, are looking for experienced data scientists who can perform business/product analysis, define key metrics, and set product team goals. Come and be a part of the top 1% of data scientists and grow with the best minds.

Check out the best jobs for October 2021here

Job description

Job responsibilities

  • Identify business challenges & opportunities for product/service improvements
  • Solve for them using analysis to make strategic or tactical recommendations
  • Apply expertise in data cleaning & wrangling, quantitative analysis, data mining
  • See beyond the numbers and understand how users interact with our consumers and products
  • Identify business challenges & opportunities for product/service improvements
  • Solve for them using analysis to make strategic or tactical recommendations
  • Apply expertise in data cleaning & wrangling, quantitative analysis, data mining
  • See beyond the numbers and understand how users interact with our consumers and products
  • Partner with Product and Engg teams to solve problems and identify trends and opportunities
  • Inform, influence, support, and execute our product decisions and product launches
  • Forecasting and setting product team goals, designing and evaluating experiments
  • Monitoring key product metrics, understanding root causes of changes in metrics
  • Building and analyzing dashboards and reports
  • Building key data sets to empower operational and exploratory analysis
  • Evaluating and defining metrics
  • Proposing what to build in the next roadmap
  • Understanding ecosystems, user behaviors, and long-term trends
  • Identifying new levers to help move key metrics
  • Building models of user behaviors for analysis or to power production systems
  • Influencing product teams through the presentation of data-based recommendations
  • Communicating the state of business, experiment results, etc. to product teams
  • Spreading best practices to analytics and product teams

Minimum requirements

  • Bachelor’s Degree/MA or Ph.D. with a focus in Business, Math, Economics, Finance, Statistics, Science or Engineering
  • Performing quantitative data analysis. report writing and presenting findings
  • Data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, MATLAB)
  • Bachelor’s Degree/MA or Ph.D. with a focus in Business, Math, Economics, Finance, Statistics, Science or Engineering
  • Performing quantitative data analysis. report writing and presenting findings
  • Data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, MATLAB)

Preferred skills

  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate large amounts of info with attention to detail and accuracy
  • Applied statistics or experimentation (i.e. A/B testing) in an industry setting
  • Communicating the results of analyses to product or leadership teams to influence the strategy
  • Strong analytical skills with the ability to collect, organize, analyze, and disseminate large amounts of info with attention to detail and accuracy
  • Applied statistics or experimentation (i.e. A/B testing) in an industry setting
  • Communicating the results of analyses to product or leadership teams to influence the strategy

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How to Become a Data Scientist in 2021?

Data scientists are analytical specialists that use their knowledge of technology and social science to identify patterns and manage data. They utilise industry expertise, contextual awareness, and criticism of current assumptions to solve business problems.

What is the scope of Data Science?

Data Science is an interdisciplinary field that combines computer science, computational mathematics, statistics, and management. To gain meaningful insights from the data, data analysis and visualisation must be conducted. Machine learning technologies are used to construct prediction models that convert raw data into actionable knowledge.

  • Data Scientist:- A data scientist is someone who has worked in a variety of fields. The data scientist can define the issue description and project objectives in accordance with the business objectives. They use artificial intelligence, machine learning, and data to discover patterns and trends and make predictions. For which a solid foundation in fields such as artificial intelligence, machine learning, statistics, and data engineering.

  • Data Analyst:- Typically, the data analyst collaborates with the business and management teams to define project objectives and business requirements. They make it easier to acquire and explore business relevant data. They convert and analyse data in order to understand patterns and trends. Data specialists can also assist teams to transform the patterns into actionable items by presenting the patterns and visualising the data.

  • Data Engineer:- Database administrators are traditionally hired by organisations to administer and handle data on a daily basis. They are in charge of assuring the integrity and performance of the organization's databases, as well as the data's security. They must be conversant with standard relational databases, disaster recovery and database backup methods, and reporting tools.

What are the roles and responsibilities of Data scientists?

The responsibilities of a Data Scientist include:

  • Undirected research for solving corporate challenges, and open-ended industry inquiries are posed.
  • Large amounts of organized and unstructured data can be extracted. They use computer languages such as SQL to query structured data from relational databases. Web scraping, APIs, and surveys are used to collect unstructured data.
  • To prepare data for predictive and prescriptive modelling, utilise advanced analytical tools, machine learning, and statistical approaches.
  • Clean the data thoroughly to remove any unnecessary information and prepare it for preprocessing and modelling.
  • EDA is used to identify how to manage missing data and to seek for patterns and/or opportunities.
  • Developing innovative methods to address issues and creating software to automate monotonous tasks
  • Predictions and results should be communicated to management and IT teams using excellent data visualisations and reports.
  • Make cost-effective modifications to current methods and tactics.

How to become a Data scientist?

To get hired as an entry-level data scientist, you'll need at least a bachelor's degree in data science or a computer science-related discipline. However most data science openings usually require a master's degree. Degrees also add structure, internships, networking, and academic credentials to your résumé. If you have a bachelor's degree in a different subject, you may need to focus on gaining job-related abilities through short term specialized courses or boot camps.

  • Learn the required skills to become a data scientist like:

    • Programming
    • Big Data Platforms
    • Cloud Tools
    • Data warehousing and structures
    • Machine Learning techniques
    • Software Engineering Skills
    • Data Mining, Cleaning and Munging
    • Research
    • Data Visualization and Reporting
    • Risk Analysis
    • Statistical analysis and Math
    • Effective Communication
  • Data scientists might focus in a certain industry or gain expertise in areas like artificial intelligence, machine learning, research, or database administration. Specialization is a smart approach to improve your tech stack and income potential while still exciting work.

  • You should be ready for your first data science position after you've obtained the necessary certifications and/or discovered your specialty! It may be beneficial to establish an online portfolio to exhibit a few projects and your achievements to potential employers. You should also look for firms with opportunities for growth. Your first data science job may not include the title data scientist, but rather an analytical function. You'll rapidly learn how to operate as part of a team and best practises that will help you move on to more senior roles.

  • Academic credentials may be more significant than you think. Is a master's degree necessary for the majority of data science jobs? It varies by profession, however, some practising data scientists have a bachelor's degree or have completed a data science bootcamp.

  • Once you've landed an interview, prepare responses to common interview questions. Because data scientist roles can be very technical, you may be asked both technical and behavioural questions. Anticipate both and practise your response loudly. Having examples from your previous job or academic experiences on hand will help you look confident and informed to interviewers.

Here are a few questions you might encounter:

  • What are the advantages and disadvantages of a linear model?
  • What exactly is a random forest?
  • To identify all duplicates in a data collection, how would you use SQL?
  • Explain your machine learning experience.
  • Give an example of a moment when you didn't know how to address a problem. What exactly did you do?

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Skills required to become a Data scientist

When looking at becoming a Data Scientist, there are certain skills you’ll need to be proficient in regardless of your role. They are:

  1. 1. Math and Statistics

    Any competent Data Scientist will have a solid basis in both math and statistics. Any company, especially one that is data-driven, would require a Data Scientist to grasp various statistical techniques — such as maximum likelihood estimators, distributors, and statistical tests — in order to assist make recommendations and choices. Calculus and linear algebra are both important since they are linked to machine learning techniques.

  2. 2. Analytics and Modeling

    Because data is only as good as the individuals who analyse and model it, a qualified Data Scientist is expected to be very proficient in this field. A Data Scientist should be able to examine data, perform tests, and develop models to acquire new insights and anticipate probable outcomes based on a foundation of both critical thinking and communication.

  3. 3. Machine Learning Methods

    While expert level expertise in this field isn't usually required, some familiarity is anticipated. Decision trees, logistic regression, and other essential aspects enabled by machine learning will be sought after by future employers.

  4. 4. Programming

    A Data Scientist must have excellent programming abilities in order to get from the theoretical to the practical. Most employers will want you to have expertise in Python, R, and other programming languages. This category includes object-oriented programming, fundamental syntax and functions, flow control statements, libraries, and documentation.

  5. 5. Data Visualization

    Data visualisation is an important part of being a Data Scientist since it allows you to effectively express essential messaging and gain buy-in for recommended solutions. Understanding how to break down complicated data into smaller, more digestible chunks, as well as how to use a number of visual aids (charts, graphs, and more), is one ability that every Data Scientist will need to be adept in order to grow in their profession. Learn more about Tableau and why data visualisation is so essential in our piece Creating Data Visualizations with Tableau.

  6. 6. Intellectual Curiosity

    At the heart of the data scientist position is a strong desire to solve issues and discover answers, particularly those that demand some creative thinking. Data doesn't mean much on its own, therefore a great Data Scientist is driven by a desire to learn more about what the data is saying them and how that knowledge may be applied on a larger scale.

  7. 7. Communication

    Data cannot communicate until it is manipulated, which implies that a good Data Scientist must have great communication abilities. Whether it's communicating to your team the actions you want to take to go from A to B with the data, or making a presentation to company leadership, communication may make or break a project.

  8. 8. Business Acumen

    A certain amount of business acumen is necessary for a Data Scientist to properly use data in a way that is useful to their company. You must completely comprehend the company's primary objectives and goals, as well as how they affect the job you accomplish. You must also be able to develop solutions that satisfy those objectives with a cost-effective and simple-to-implement approach that assures broad acceptance.

  9. Interested in remote data scientist developer jobs?

    Become a Turing developer!

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How to get Data scientist jobs?

Turing offers the best remote Data scientist opportunities to supplement your career as an experienced Data scientist. Working on difficult new technology and business challenges can assist you in growing rapidly. Join our network of the world's best developers to find long-term, full-time remote Data scientist jobs with higher compensation and promotion prospects.

Why become a Data scientist at Turing?

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Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

Elite US jobs

Long-term opportunities to work for amazing, mission-driven US companies with great compensation.

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Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

Career growth

Work on challenging technical and business problems using cutting-edge technology to accelerate your career growth.

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Exclusive developer community

Join a worldwide community of elite software developers.

Exclusive developer community

Join a worldwide community of elite software developers.

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Exclusive developer community

Join a worldwide community of elite software developers.

Exclusive developer community

Join a worldwide community of elite software developers.

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Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

Once you join Turing, you’ll never have to apply for another job.

Turing's commitments are long-term and full-time. As one project draws to a close, our team gets to work identifying the next one for you in a matter of weeks.

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Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

Great compensation

Working with top US corporations, Turing developers make more than the standard market pay in most nations.

How much does Turing pay their Data scientists?

Every Turing data scientist has the opportunity to set their own pace. Turing, on the other hand, will propose a salary at which we are certain we can find you a successful and long-term position. Our suggestions are based on our analysis of market conditions as well as customer preferences.

Frequently Asked Questions

What skills are needed to be a Data Scientist?
To be proficient in Data Science, you need to have a stronghold on Python, Power BI, OpenCV, and Tableau. In addition, a good understanding of Probability, Statistics, Data Wrangling, Database Management, Data Visualization, and Cloud Computing is a great plus.
Is Data Science a stressful job?
Long working hours are frequent when working on big problems/projects, and performance expectations are always high. But many companies, especially Silicon Valley companies, offer great work culture to reduce stress and keep employees motivated. To work with such companies, visit Turing.com. Via Turing, you can get full-time, long-term remote Data Scientist jobs.
How is Turing different from other remote based job providers?
It is the combination of our core business model and values that makes us different from others. We provide full-time, long-term projects to remote developers whereas most of our competitors offer more freelance jobs.
Is Data Science a good career?
Yes. Becoming a Data Scientist is highly lucrative both in terms of career growth and finance. Silicon Valley companies are always looking for talented Data Scientists and are ready to pay excellent salaries. To apply for such jobs, visit Turing.com. You can join a network of the world’s best Data Scientists and get full-time, long-term remote Data Scientist jobs at Turing.com
What is Turing?
We are a Palo Alto-based 'deep' jobs platform allowing talented software developers to work with top US firms from the comfort of their homes. We are led by Stanford alumni and successful A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan.
How many rounds do I need to clear before selection?
After uploading your resume, you will have to go through the three tests -- seniority assessment, tech stack test, and live coding challenge. Once you clear these tests, you are eligible to apply to a wide range of jobs available based on your skills.
Do I need a degree to become a Data Scientist?
No. You don't need a college degree to become a Data Scientist. However, if you are skilled with data science concepts and have more than 3 years of experience, you apply for a high paying, long term remote job in Silicon Valley companies via Turing.com.
What kind of developers does Turing hire?
We, at Turing, hire remote developers for over 100 skills like React/Node, Python, Angular, Swift, React Native, Android, Java, Rails, Golang, PHP, Vue, among several others. We also hire engineers based on tech roles and seniority.
What level English is necessary to get a job?
Communication is crucial for success while working with American clients. We prefer candidates with a B1 level of English i.e. those who have the necessary fluency to communicate without effort with our clients and native speakers.
View more FAQs

Leadership

In a nutshell, Turing aims to make the world flat for opportunity. Turing is the brainchild of serial A.I. entrepreneurs Jonathan and Vijay, whose previous successfully-acquired AI firm was powered by exceptional remote talent. Also part of Turing’s band of innovators are high-profile investors, such as Facebook's first CTO (Adam D'Angelo), executives from Google, Amazon, Twitter, and Foundation Capital.

Equal Opportunity Policy

Turing is an equal opportunity employer. Turing prohibits discrimination and harassment of any type and affords equal employment opportunities to employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, disability status, protected veteran status, or any other characteristic protected by law.

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