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Hire the Top 7% of Vetted Agencies for Data Scientists

Engage vendors to complete a project or augment an existing team. The process is free, simple and you'll be reviewing proposals in 72 hours

EMPOWERING THE STARTUP ECOSYSTEM

HIRE Data Scientists VENDORS

Why Founders, CEOs and CTOs love Pangea.ai


Talent quality

Rigorous vetting to select top 7%

Speed

Hire, or augment a team in 72h

Flexibility

Scale up and down, on-demand

Guide to hiring great Data Scientists vendors


Discover how to hire data scientists with this ultimate guide for businesses, empowering your organization to harness data and drive innovation effectively.

"Our engagement with Pangea.ai has significantly helped us improve the delivery quality of our innovations."

Pete Becker

Innovation Product Management Lead

"We worked with the Pangea.ai team to identify a mobile engineering partner to help with our iHeartRadio for auto roadmap."

Tom Drapeau

VP Engineering

"Working with Pangea.ai was great. They made sense out of a complicated and fragmented market and we were able to find a good fit for our needs."

Cordel Robbin-Coker

Co-Founder and CEO

"Pangea.ai helped us with their very clear and structured selection process to find our perfect partners for our product in just a few steps."

Reiner Neusser

CEO

Why Founders, CEOs and CTOs love Pangea.ai


Talent quality

Rigorous vetting to select top 7%

Speed

Hire, or augment a team in 72h

Flexibility

Scale up and down, on-demand

"Our engagement with Pangea.ai has significantly helped us improve the delivery quality of our innovations."

Pete Becker

Innovation Product Management Lead

"We worked with the Pangea.ai team to identify a mobile engineering partner to help with our iHeartRadio for auto roadmap."

Tom Drapeau

VP Engineering

"Working with Pangea.ai was great. They made sense out of a complicated and fragmented market and we were able to find a good fit for our needs."

Cordel Robbin-Coker

Co-Founder and CEO

"Pangea.ai helped us with their very clear and structured selection process to find our perfect partners for our product in just a few steps."

Reiner Neusser

CEO

"Pangea.ai connected us to various experts around the world."

Ayne Santiago

Senior Lead Software Engineer

"The team at Pangea.ai helped us meet and engage with a high quality shortlist enabling us to spend our time building a relationship."

Phillip Mundy

Founder

"Pangea.ai is a wonderful partner for any early stage startups like us who are eager for top engineers to accelerate our product roadmap."

Jeff Hu

Founding Engineer

"Pangea.ai offers a fantastic service for high growth businesses such as ourselves. Their expertise saved us a significant amount of time and risk."

Paul Skidmore

Product Lead

"Working with Pangea.ai was an awesome and pleasant experience. We got exactly what we wanted and more."

Javy Olives

Enterprise Product Head

"The Pangea.ai team is professional and effective. Pangea's offering of top talent delivers."

Raymond Spoljaric

CEO

Guide to hiring great Data Scientists vendors


Discover how to hire data scientists with this ultimate guide for businesses, empowering your organization to harness data and drive innovation effectively.

YOU MAY HAVE SEEN US BEFORE

OUR MATCHING PROCESS

We match you to the right team.

Not all agencies are right for all jobs.

We partner with you to fully understand your needs and key criteria, then we match you to the agencies in our community we think will be a perfect fit.

Create Brief

Whether you're just browsing or have a full set of specs prepared -- our simple, streamlined, and dynamic briefing process ensures we capture and understand your critical needs. And if you’re ever stuck or need help, our team is standing by to support you.

Matching Choice
Matching Choice Step 1

FAQs

To select the top percentile of Data Scientists agencies, our proprietary due diligence consists of a rigorous 5-step process: pre-qualification, organizational mapping, client reviews, team health assessment, and acceptance. Only the top 7% of agencies complete the process successfully. Once accepted, ongoing efforts to ensure continued excellence and standing within the community begin. This is achieved by consistently demonstrating excellence in their work and continued commitment to due diligence efforts by Pangea.ai.

Once you share your requirements, the brief is shared with our community of 150+ agencies (without any personal identifiable information). Said agencies have 48 hours to apply to your brief, and you can access each brief on our platform. Using a combination of AI and human expertise, our system matches and connects you with the 3 most suitable Data Scientists agencies from the application pool. As a result, we can always guarantee delivery within 72 hours—ensuring the most efficient process for connecting with the right agencies for any requirements.

When matching fully-managed agency teams, we prioritize their expertise in the following order: 

  1. Product Domain: What is being built? 
  2. Industry: What industry is it being built in? 
  3. Services: What are the services required? 
  4. Roles: What is the ideal team structure? 
  5. Tech Stack: What technology is required? 

When matching for a specific agency role, we prioritize talent expertise in the following order: 

  1. Roles: Who is being hired? 
  2. Tech Stack: Which technology is required for the role? 
  3. Product Domain: Is domain know-how required for the role? 
  4. Industry: Is industry know-how required for the role? 
  5. Services: Does the role have to provide any services? 

Additionally, we consider rates and location preference, budget indication, kick-off timeline, and other relevant factors to curate the best-match agencies for both engagement models.

Countries such as Uruguay, Brazil, Poland, Crotia, Portugal, Poland, and similar are home to high-quality talent clusters in software development. The vetted agency community at Pangea.ai reflects said notion, with our agency partners being located in Latin America and Europe. The rates depend on location, country, skills, and seniority required, but the average hourly rate is between €40-80 which is an average daily rate of €320-640.

Pangea.ai is a free service for businesses as we are compensated an annual membership fee for continuous due diligence by the agency partners and a % of their sales and marketing spend. 

How to Hire Data Scientists? The Ultimate Guide for Businesses


TABLE OF CONTENTS


Defining the Role and Requirements




Conclusion


FAQs:


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Companies face challenges in harnessing the power of data to drive innovation and stay competitive. Data science companies and experts in extracting insights and making predictions from complex data are instrumental in addressing these challenges. 

As per the McKinsey Global Institute, organizations that harness the power of data have a significantly higher chance of success. They are 23 times more likely to attract new customers, six times more likely to maintain customer loyalty, and an impressive 19 times more likely to achieve profitability.

A data scientist is a professional who specializes in collecting, analyzing, and interpreting large and complex datasets to derive valuable insights and make data-informed decisions They possess a unique combination of skills, including expertise in statistics, programming, machine learning, and data visualization, as well as domain knowledge relevant to their industry. 

However, it is challenging to hire data scientists that are right for your business. This article will help you learn how to hire data scientists and build a strong data science team.

Understanding the Core Skills and Competencies

A woman is learning the core skills and competencies using a laptop to hire data scientists.

To hire data scientists for your organization, it's essential to understand the core skills and competencies they should possess. These can be broadly categorized into technical skills, domain knowledge, and soft skills.

Domain knowledge

Depending on your organization's industry, the ideal data scientist should have domain knowledge that helps them understand and interpret the data more effectively. 

For instance, a data scientist in a healthcare organization should be familiar with medical terminology and concepts, while one in finance should understand financial instruments and market dynamics.

Read more about the future of Data Science in our article. 

Soft skills

Hire data scientists who possess strong soft skills along with technical skills and domain knowledge. Excellent communication and presentation skills will allow them to effectively convey insights to non-technical stakeholders. Problem-solving and critical thinking abilities will enable them to tackle complex challenges, while collaboration and teamwork skills will ensure they work well with cross-functional teams.

Technical skills

Data scientists need to be proficient in various programming languages, such as Python, R, and Java. Familiarity with data manipulation and analysis tools like SQL and Excel is also crucial. A strong candidate should have experience with machine learning frameworks like TensorFlow and PyTorch, as well as big data platforms like Hadoop and Spark.

For example, if your organization primarily uses Python for data analysis, you should focus on candidates with strong Python skills and experience using popular libraries like Pandas and NumPy.

Defining the Role and Requirements

Before you hire data scientists, it's crucial to define the role and requirements clearly. Craft a detailed data scientist's job description that outlines the responsibilities and expectations for the role. Be sure to tailor the description to your organization's specific needs, and specify the level of expertise required for each skill. 

For example, if your organization deals with vast amounts of unstructured data, emphasize the importance of experience with big data platforms.

In addition, clearly define the key projects and goals the data scientist will be responsible for and the reporting structure within the organization. This will help candidates understand the scope of their work and ensure alignment with your organization's objectives.

How to Hire Data Scientists: The Recruitment Process

A recruiter is interviewing a candidate in the meeting room to hire data scientists that fits their organization's needs.

With the role and requirements defined, it's time to embark on the recruitment process. This process involves several steps designed to help you find the best candidates for your data science team.

Sourcing candidates

  1. Tapping into your network: Reach out to colleagues, industry connections, and professional groups to find potential candidates. Personal recommendations can provide valuable insights into a candidate's abilities and work ethic.
  2. Utilizing job boards and LinkedIn: Post the job to hire data scientists on popular job boards to attract a wider pool of candidates. Platforms like Pangea.ai make this process even easier by connecting you with the best five experts tailored to your needs.
  3. Attending conferences and meetups: Participate in data science conferences, meetups, and workshops to network with potential candidates and gain insights into the latest industry trends.

Screening and evaluation

  1. Assessing resumes and portfolios: Review candidates' resumes and portfolios to evaluate their experience, skills, and accomplishments. Look for relevant projects and achievements that demonstrate their proficiency in the required skills.
  2. Conducting technical tests and challenges: Use technical tests and challenges to assess candidates' abilities in programming, data manipulation, and machine learning. For example, you can use platforms like HackerRank or Codility to create customized coding challenges.
  3. Evaluating domain knowledge through case studies: Provide candidates with case studies related to your industry to assess their domain knowledge and ability to derive insights from real-world data. This can help you gauge how well they can apply their skills to solve problems specific to your organization. Read about the best data science development frameworks in our article. 

Interviews

  1. Technical deep dives: Conduct in-depth discussions on candidates' past projects and experiences to evaluate their technical expertise and understanding of data science concepts.
  2. Assessing cultural fit and collaboration skills: Ensure that the candidate is a good fit for your organization's culture and can work effectively with cross-functional teams. You may include team members from different departments in the interview process to gather diverse perspectives on the candidate's fit.
  3. Behavioral and situational questions: Include behavioral and situational questions in the interview process to hire data scientists. This will help you to assess candidates' soft skills, such as communication, problem-solving, and teamwork.

Making an offer

  1. Negotiating salary and benefits: Offer a competitive salary and benefits package based on industry standards and the candidate's experience. Be prepared to negotiate, as top data science talent is often in high demand.
  2. Ensuring a smooth onboarding process: Create a well-structured onboarding plan to help the new data scientist integrate into your organization and start contributing to projects quickly.

Companies that Hire Data Scientists and Achieving Success

Top companies across various industries have recognized the value of data scientists and have successfully integrated them into their organizations. These companies serve as examples of how hiring the right data science talent can drive innovation and business growth. 

Tech Giants

  1. Google: Google employs data scientists to optimize search algorithms, develop machine learning models for applications like Google Translate, and improve user experiences across their product suite. Their data-driven approach has allowed them to maintain their position as a market leader in the tech industry.
  2. Amazon: Amazon leverages data scientists to optimize its recommendation engine, streamline supply chain processes, and develop new services like Amazon Go. With its commitment to data-driven decision-making, Amazon has achieved massive growth and expansion into various market segments.

Industry leaders

  1. Airbnb: Data scientists at Airbnb work on projects like dynamic pricing algorithms, fraud detection, and user experience optimization. By leveraging data science, Airbnb has disrupted the traditional hospitality industry and achieved rapid global growth.
  2. Netflix: Netflix hires data scientists to enhance their content recommendations, conduct A/B testing, and analyze user behavior. Their data-driven strategies have led to a highly personalized user experience, helping them become a dominant force in the streaming industry.

Emerging startups

  1. Stitch FixStitch Fix is an online personal styling service that relies on data scientists to develop algorithms that match users with the right clothing items based on their preferences and previous purchases. Stitch Fix's success demonstrates the potential of data-driven personalization in the retail industry.
  2. Lemonade: As an insurance company, Lemonade uses data scientists to analyze risk factors, optimize pricing models, and detect fraudulent claims. Their data-driven approach has allowed them to innovate within the insurance industry and attract a growing customer base.

Conclusion

By understanding the core skills and competencies, defining the role and requirements, and following a structured recruitment process, you can hire data scientists that thrive in a collaborative and growth-oriented environment. In the fast-paced world of data science and big data, continuous adaptation and learning are essential to stay ahead of the curve and ensure the long-term success of your team.

FAQs:

Q1. How do I hire a good data scientist?

To hire a good data scientist, follow these steps:

  1. Understand the core skills and competencies required for the role, including technical skills, domain knowledge, and soft skills.
  2. Define the role and requirements, including job description, responsibilities, and expectations tailored to your organization's needs.
  3. Utilize various sourcing methods such as your network, job boards, conferences, and meetups to find potential candidates.
  4. Screen and evaluate candidates through resume reviews, technical tests, case studies, and interviews, focusing on their skills, experience, and cultural fit.
  5. Offer a competitive salary and benefits package and ensure a smooth onboarding process.
  6. Foster a supportive and collaborative work environment to help your data scientists thrive and contribute effectively to your organization.

Q2. Is it hard to hire a data scientist?

Hiring a data scientist can be challenging due to several factors:

  1. High demand: Data science is a rapidly growing field, and the demand for skilled data scientists often outpaces the available talent pool.
  2. Diverse skill set: Data scientists need to possess a wide range of skills and expertise, making it difficult to find candidates who excel in all required areas.
  3. Industry-specific knowledge: Depending on your organization's industry, finding data scientists with relevant domain knowledge can be challenging.
  4. Cultural fit: Identifying candidates who fit well within your organization's culture and can collaborate effectively with cross-functional teams is crucial but can be difficult to assess.

However, by following a structured hiring process and focusing on key skills and competencies, you can increase your chances of finding the right candidate for your organization.

Q3. Does Netflix hire a data scientist?

Yes, Netflix hires data scientists to help drive data-informed decision-making, improve customer experiences, and enhance their content recommendations. Data scientists at Netflix work on a variety of projects, including personalization algorithms, content promotion, user behavior analysis, and A/B testing. The company looks for candidates with strong technical skills, domain expertise, and a passion for using data to solve complex problems and create innovative solutions.

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