Hire Data Scientists

Gain the competitive edge that only advanced data science can provide. Our dedicated professionals can help you leverage advanced analytical techniques and unlock hidden value in your information assets.

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    commitment to security & privacy

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How to Hire a Data Scientist with Beetroot

We work with a diverse network of data scientists where each brings unique knowledge and business acumen. Our data scientists possess expertise in various domains, including Machine Learning (ML), deep learning, Natural Language Processing, and statistical modeling. Because every moment counts, we’re committed to a rapid process for matching you with the best-fit candidates. Meet the data scientists you can work with:

  • $58/h

    Mid-Level Data Scientist

    Nazar B., 5+ years of experience
    Proficient in statistical and ML techniques to solve business problems. Experience in collecting, cleaning, and analyzing large datasets, building predictive models, and communicating findings to stakeholders. Adept at working with various data sources and utilizing data visualization tools.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Data processing (PySpark)
    • Jupyter
    • Keras / TensorFlow / PyTorch
    • NumPy
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $42/h

    Middle ML Engineer

    Daniel M., 3+ years of experience
    Experienced with crafting end‑to‑end CNN pipelines in Python, leveraging PyTorch / TensorFlow and frameworks such as YOLO, RetinaFace, and SSD to deliver fast, accurate object‑ and face‑detection models.
    • CUDA / ONNX / TensorRT
    • Keras / TensorFlow / PyTorch
    • Matplotlib
    • NumPy
    • OpenCV
    • Python
    • RetinaFace
    • scikit‑image
    • SciPy
    • SSD (Single Shot Detectors)
    • Torchvision
    • YOLO

    Request full CV

  • $32/h

    Junior Data Analyst

    Artem K., 2+ years of experience
    A motivated and detail-oriented Junior Data Analyst. Eager to apply his strong analytical foundation to real-world business challenges. Has a solid understanding of statistical concepts and data manipulation techniques. Skilled in data cleaning, preparation, and basic analysis. Proficient in data visualization tools and is committed to learning and growing within the field.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $48/h

    Machine Learning Engineer (Mid-level)

    Alex F., 4+ years of experience
    Alex has worked on projects ranging from customer segmentation to demand forecasting. He builds and refines ML models using Python, TensorFlow, and scikit-learn. He’s strong in data preprocessing and feature engineering and is comfortable deploying models in production using Docker and AWS.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • Keras / TensorFlow / PyTorch
    • NumPy
    • Orchestration: Kubernetes, Docker
    • Pandas
    • Python
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

  • $43/h

    Data Analyst & BI Specialist (mid‑level)

    Minh Khoa N., 5 years of experience
    Data‑driven professional translating raw numbers into business‑ready insights. Skilled in SQL, Python, and modern BI tooling, Khoa builds automated dashboards and predictive models that cut reporting time and boost revenue.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • BI tools (Power BI, Tableau, Looker Studio)
    • CI/CD
    • Data quality
    • Jupyter
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $85/h

    Senior Data Scientist

    Magdalena R., 10+ years of experience
    A highly experienced data scientist with a proven track record of leading complex data science projects from inception to deployment. Expertise in developing and implementing advanced ML models, conducting statistical analysis, and providing actionable insights to drive business decisions.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • Cloud Platforms: AWS, Azure, GCP
    • Keras / TensorFlow / PyTorch
    • Processing: Hadoop, Spark, PySpark
    • Python
    • R
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

  • $55/h

    Senior Data Analyst

    Olha B., 8+ years of experience
    A highly experienced Senior Data Analyst with a track record of driving strategic business outcomes through advanced data analysis and modeling. Possesses deep expertise in statistical inference, predictive modeling, and data storytelling, effectively communicating complex findings to both technical and non-technical audiences.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Cloud Platforms: AWS, Azure, GCP
    • Data governance
    • Data warehousing
    • NumPy
    • Pandas
    • Python
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

  • $58/h

    Mid-Level Data Scientist

    Nazar B., 5+ years of experience
    Proficient in statistical and ML techniques to solve business problems. Experience in collecting, cleaning, and analyzing large datasets, building predictive models, and communicating findings to stakeholders. Adept at working with various data sources and utilizing data visualization tools.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Data processing (PySpark)
    • Jupyter
    • Keras / TensorFlow / PyTorch
    • NumPy
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $42/h

    Middle ML Engineer

    Daniel M., 3+ years of experience
    Experienced with crafting end‑to‑end CNN pipelines in Python, leveraging PyTorch / TensorFlow and frameworks such as YOLO, RetinaFace, and SSD to deliver fast, accurate object‑ and face‑detection models.
    • CUDA / ONNX / TensorRT
    • Keras / TensorFlow / PyTorch
    • Matplotlib
    • NumPy
    • OpenCV
    • Python
    • RetinaFace
    • scikit‑image
    • SciPy
    • SSD (Single Shot Detectors)
    • Torchvision
    • YOLO

    Request full CV

  • $32/h

    Junior Data Analyst

    Artem K., 2+ years of experience
    A motivated and detail-oriented Junior Data Analyst. Eager to apply his strong analytical foundation to real-world business challenges. Has a solid understanding of statistical concepts and data manipulation techniques. Skilled in data cleaning, preparation, and basic analysis. Proficient in data visualization tools and is committed to learning and growing within the field.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $48/h

    Machine Learning Engineer (Mid-level)

    Alex F., 4+ years of experience
    Alex has worked on projects ranging from customer segmentation to demand forecasting. He builds and refines ML models using Python, TensorFlow, and scikit-learn. He’s strong in data preprocessing and feature engineering and is comfortable deploying models in production using Docker and AWS.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • Keras / TensorFlow / PyTorch
    • NumPy
    • Orchestration: Kubernetes, Docker
    • Pandas
    • Python
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

  • $43/h

    Data Analyst & BI Specialist (mid‑level)

    Minh Khoa N., 5 years of experience
    Data‑driven professional translating raw numbers into business‑ready insights. Skilled in SQL, Python, and modern BI tooling, Khoa builds automated dashboards and predictive models that cut reporting time and boost revenue.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • BI tools (Power BI, Tableau, Looker Studio)
    • CI/CD
    • Data quality
    • Jupyter
    • Pandas
    • PostgreSQL / MySQL / SQL (general) / Snowflake / Redshift
    • Python
    • Scikit-learn / Statsmodels

    Request full CV

  • $85/h

    Senior Data Scientist

    Magdalena R., 10+ years of experience
    A highly experienced data scientist with a proven track record of leading complex data science projects from inception to deployment. Expertise in developing and implementing advanced ML models, conducting statistical analysis, and providing actionable insights to drive business decisions.
    • Apache Kafka / AWS Kinesis / Airflow / AWS Glue
    • Cloud Platforms: AWS, Azure, GCP
    • Keras / TensorFlow / PyTorch
    • Processing: Hadoop, Spark, PySpark
    • Python
    • R
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

  • $55/h

    Senior Data Analyst

    Olha B., 8+ years of experience
    A highly experienced Senior Data Analyst with a track record of driving strategic business outcomes through advanced data analysis and modeling. Possesses deep expertise in statistical inference, predictive modeling, and data storytelling, effectively communicating complex findings to both technical and non-technical audiences.
    • BI tools (Power BI, Tableau, Looker Studio)
    • Cloud Platforms: AWS, Azure, GCP
    • Data governance
    • Data warehousing
    • NumPy
    • Pandas
    • Python
    • Scikit-learn / Statsmodels
    • SQL (query optimization, window functions)

    Request full CV

Is It Time to Hire Data Scientists?

Organizations often reach a tipping point where they recognize patterns in their data but lack the specialized expertise.This usually occurs when basic analytics no longer answer the critical questions driving your business decisions. You may have data spread across multiple systems that needs integration and advanced analysis to reveal hidden value.

The maturity of your data infrastructure also plays a crucial role in this decision. While you don’t need perfect data to begin, having basic data collection systems in place provides data scientists with the raw materials they need to generate value. If you’re investing significant resources in collecting data but aren’t leveraging it for strategic decision-making, it’s likely time to bring in data science expertise. Key situations that signal it’s time to hire offshore data scientists include:

  • When your business decisions increasingly rely on predicting future outcomes rather than just understanding past performance.

  • When you’ve accumulated substantial data assets across your organization but lack the specialized skills to extract maximum value from them.

  • When you’re facing complex business problems that require sophisticated statistical modeling, Machine Learning, or AI solutions beyond the capabilities of your current team.

  • When you need to automate decision processes or develop intelligent products and services that can adapt to user behavior or changing conditions.

Find your data scientist:

Our Expertise in Data Science

With backgrounds ranging from computational statistics and mathematics to computer science and specialized domain knowledge, our team brings a multidisciplinary approach to every project.

  • AI Strategy Consulting

    Our data scientists provide strategic guidance on how to effectively leverage AI and ML within your organization. This includes identifying high-value use cases, developing implementation roadmaps, addressing ethical considerations, and building necessary capabilities.

  • Data Pipeline Development

    You can design and implement data pipelines that automate the collection, processing, transformation, and storage of data from multiple sources with Beetroot. By establishing proper data infrastructure, organizations can eliminate data silos and ensure consistent data quality across the enterprise.

  • Predictive Analytics Solutions

    Your organization can build custom predictive models that forecast business outcomes with high accuracy. These predictive capabilities will allow you to proactively address challenges, optimize resource allocation, and identify opportunities before they become apparent to competitors.

  • Computer Vision Applications

    Computer vision makes it possible for you to create systems that can analyze and interpret data from images and video streams. Some of the applications include quality control in manufacturing, visual inspection processes, object detection for retail analytics, and medical image analysis.

  • Recommendation Systems

    Recommendation engines can help you suggest relevant products, content, or actions based on user preferences. These systems drive increased engagement, higher average order values, and improved customer satisfaction through personalized recommendations.

  • Time Series Forecasting

    Custom time series models can predict future values for critical business metrics, accounting for seasonal patterns, long-term trends, and external factors. They provide essential inputs for inventory management, resource planning, budgeting, and strategic decision-making.

  • ML Models

    Through advanced techniques like hyperparameter tuning, feature engineering, and algorithm selection, we can improve the performance of your ML model. For clients with existing solutions, this service extends the lifespan and value of their AI investments while reducing computational resource requirements.

  • Anomaly Detection Systems

    Anomaly detection systems can continuously monitor data streams to identify unusual patterns that may indicate fraud, equipment failure, security breaches, or other critical issues. These systems can minimize downtime from equipment failures and enhance your overall operational resilience.

Cost of Hiring Data Scientists

The decision to find a data scientist for hire or cooperate with a team of these professionals involves several key factors that influence the cost:

  • Expertise Level. Junior, mid-level, and senior data scientists command different salary ranges due to their varying levels of experience and skill.
  • Project Scope and Complexity. More complex projects requiring specialized skills (e.g., natural language processing, deep learning) or industry-specific knowledge may necessitate hiring senior or specialized data scientists, increasing costs.

If you consider cooperating with Beetroot, you can rely on transparent pricing.

  • Team Size. The number of data scientists required depends on the project’s scale and timeline. Larger teams naturally incur higher costs.
  • Employment Model. Hiring in-house data scientists involves salaries, benefits, and overhead costs. Alternatively, engaging freelancers or dedicated teams can offer more flexible and potentially cost-effective solutions.
  • Junior

    If you consider cooperating with Beetroot, you can rely on transparent pricing. For short-to-mid-term projects, rates for junior specialists begin at $180 per day, or $3,400 per month. Long-term engagements for junior specialists are priced from $2,550 per month.

  • Middle

    Mid-level data scientists are billed from $290 daily, or $5,500 monthly, for short-to-mid-term needs, and from $4,150 monthly for long-term collaboration

  • Senior

    Senior data scientists’ rates start at $435 per day, or $8,250 per month, for short-to-mid-term projects, and from $6,200 monthly for an extended project.

Freelancers vs. White-Label Tech Partner

When seeking data science expertise, you might consider engaging individual freelancers or partnering with a white-label tech company. The most suitable choice often depends on the scale of your project, your internal resources, and your long-term strategic goals.

Freelancers

White-Label Tech Partner

Strengths
  • Cost-effective for targeted, well-defined tasks
  • Direct communication with individual designer
  • Highly specialized expertise in specific niches
  • Consistent resource availability
  • Established quality assurance processes
  • Integrated workflow with development teams
Considerations
  • Project management responsibilities fall on client
  • Scalability can be limited and dependent on individual availability
  • Can involve a potentially higher overall investment
  • More formal communication channels
Ideal for
  • Short-term projects with specific deliverables
  • Early-stage startups with fluctuating design needs
  • Long-term product development and evolution
  • Organizations that search for consistent design quality

Build your data science team:

Cooperation Models

Every organization has unique needs when it comes to data science talent. That’s why we offer various engagement options designed to align with your goals, timeline, and budget.

  • Dedicated Development Teams

    Direct communication and control

    Our dedicated team model empowers you to hire full-time data scientists who work exclusively on your projects while remaining employed by our company. This approach gives you all the benefits of an in-house data science team without the overhead of recruitment, onboarding, and HR management.

  • Project-Based Engagements

    End-to-end support

    We handle your entire project from start to finish, delivering a solution that meets your specific requirements. Our structured methodology breaks projects into manageable phases with regular checkpoints to ensure alignment and quality.

  • Hands-on team training

    We design and deliver training programs to upskill your existing teams in specific technologies and practices. You can also tap into the variety of ready-made workshops, such as “Gen AI for devs,” “GenAI for productivity,” and “Cybersecurity for teams”.

Our Hiring Process

We offer a simple three-step journey. Once you select your ideal candidates, we handle all administrative aspects of the onboarding process. You get:

  • Meticulous Candidate Vetting

    Our recruiters conduct thorough preliminary assessments, evaluating each candidate’s professional background, communication skills, and English proficiency.

  • Talent Network

    We have a dynamic database of data scientists who have successfully completed our evaluation process. This curated talent pool will allow you to rapidly find the experts you need.

  • Onboarding Support

    We handpick experts who precisely meet your project requirements and offer further support, taking care of administrative tasks such as invoicing and workstation setup.

Why Hire Data Science Developers with Beetroot

With over 12 years of experience connecting organizations with software developers, we have a deep expertise in building high-performing remote teams and empowering businesses with expert technical talent.

  • All-in-One Capability

    Beetroot offers end-to-end support across your entire data science journey. From initial strategy development through implementation, deployment, and ongoing optimization, our team provides assistance at every stage of company and product development. This approach ensures top-tier across all aspects of your data initiatives.

  • Sustainability at Our Core

    We believe technology should drive positive environmental and social impact. We carefully select data centers and cloud providers to minimize the ecological footprint of data-intensive projects. By choosing Beetroot, you partner with a company that aligns with modern corporate responsibility values while still delivering exceptional technical solutions.

  • Security

    Data science projects often involve sensitive information and critical business assets. We implement rigorous security protocols that align with industry standards, including comprehensive NDA coverage, secure development environments, and regular security audits. Our data scientists follow strict data handling procedures and are trained in privacy-preserving techniques.

  • Industry-Specific Expertise

    Our data scientists bring domain knowledge across multiple industries, including finance, healthcare, and greentech. This specialized experience means they understand the unique challenges, regulations, and opportunities within your sector. You benefit from professionals who speak your language.

  • Cultural Compatibility

    Technical expertise alone doesn’t guarantee project success. We carefully evaluate the working styles, communication preferences, and cultural elements of your organization to match you with data scientists who will integrate smoothly with your team. This alignment accelerates the time-to-productivity for new team members.

  • Flexible Terms

    We recognize that business needs and market conditions change. Our commercial agreements are designed with flexibility in mind, allowing you to scale teams up or down as requirements evolve. We offer multiple engagement models. This approach allows for effective resource planning on both sides.

Our Clients Say

Discover our impact through the lens of client success.

  • Beetroot AB has an education academy where they constantly develop new talent, which is very unique. The talent Beetroot AB provides is very skillful and up-to-date with technologies. I hadn’t seen the same extent with other service providers. Beetroot AB even suggests updates for our company regarding technologies when they’re training their team in a new tool.

    Victor Botev,
    CTO & Founder, Iris.ai

Let’s discuss your data science needs

Recruit data scientists with Beetroot. Fill out the form to get the details.

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