Hire the Best Data Scientists

Clients rate our Data Scientists
Rating is 4.8 out of 5.
4.8/5
Based on 6,962 client reviews
Hugo M.

Reston, Virginia

$60/hr
5.0
18 jobs

Data Solutions: Automation, Scraping, Engineering, Analysis, Visualization, and Cleanup ๐Ÿš€ ๐Ÿ‘‹Hello! Welcome to your one-stop solution for leveraging data and streamlining business processes. Specializing in empowering businesses to achieve their operational goals, from automating tedious manual tasks to deriving insights through data analysis and visualizations, I'm here to assist in guiding you towards data-driven decision-making. Data optimization processes don't need to be costly or reliant on subscription services. With experience in supporting non-profits and small-to-medium-sized businesses, I provide cost-effective solutions tailored to your immediate needs and long-term objectives. Expertise: โœ… Data Automation & Integration โœ… Data Visualization and Dashboard Development โœ… Data Clean-Up โœ… Web Scraping & API Calls โœ… Custom Web Applications (for solutions, visualizations, and automations) โœ… Data Modeling and Architecture Proficiency: โœ… Python โœ… R Programming Language โœ… HTML and CSS โœ… Google Analytics โœ… Marketo โœ… Flask Framework โœ… Plotly โœ… Power BI โœ… Tableau โœ… Salesforce โœ… Jobber โœ… And many more! Interested in elevating your data game? I'm here to help. Reach out and letโ€™s discuss how we can achieve your goals together.

  • Data Science
  • Python
  • SQL
  • Microsoft Excel
  • Data Analysis
  • Machine Learning
  • pandas
  • Data Scraping
  • Web Application
  • Data Visualization
  • Business Intelligence
  • Microsoft Power BI
  • Tableau
  • Analytics Dashboard
  • Salesforce CRM
Hari N.

Butwal, Nepal

$19/hr
4.9
113 jobs

Hi! Greeting ๐–๐„๐‹๐‚๐Ž๐Œ๐„ ๐“๐Ž ๐“๐‡๐„ ๐“๐Ž๐-๐‘๐€๐“๐„๐ƒ ๐๐‹๐”๐’ ๐’๐„๐‹๐‹๐„๐‘ ๐๐‘๐Ž๐…๐ˆ๐‹๐„!!! I am an experienced Data Scientist and Machine Learning expert with more than 12 years of experience with different companies and projects. ๐—›๐—ฒ๐—ฟ๐—ฒ ๐—œ ๐—ฎ๐—บ ๐—ผ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ถ๐—ป๐—ด โœ… Machine Learning with Python โœ… Data Preprocessing with Python, R, pandas, tableau etc. โœ… Database management with SQL and MySQL โœ… Data visualization (Matplotlib, scipy, ggplot, heatmap, ipython, seaborn, Excel, Power BIetc.) โœ… Mathematics for Data Science, including Algebra and Statistics โœ… Model deployment โœ… Preparing report in LaTeX or Word I work on the following aspects โœ… Unsupervised machine learning, including K-means, PCA, HMM, etc. โœ… Supervised Machine learning and deep learning, including SVM, Decision Tree, Random Forest, XG Boost, NaiveBays, etc. โœ… Forecasting models including MA, ARMA, ARIMA, SARIMA, etc. โœ… Data extraction โœ… Decision-making based on the results of data. Let's connect for a call and explore how my seasoned expertise can work wonders for you! Regards Hari N

  • LaTeX
  • Data Analytics
  • Machine Learning
  • Mathematics
Samuel A.

Madrid, Spain

$35/hr
5.0
164 jobs

โญ Top 1% of Data Science talent on Upwork โญTrusted by 50+ clients worldwideโญ 120+ projects and 7+ years of experienceโญClear communication, transparent pricing, and top quality. I have worked across different sectors, including: 1.1 InnoSight Financial Planning (USA): I designed an optimal portfolio based on back-projected AI-powered financial indices. 1.2 Aeuthux (USA): I led a team of data scientists to build a web platform supporting investment decision-making. 1.3 Placeholder LLC (USA): I built a trading bot using machine learning deployed on AWS to operate in cryptocurrency markets. 1.4 ARCA-X (QATAR) I wrote research papers on the financial structure of non-central banking systems.

  • Data Science
  • Python
  • R
  • Economic Analysis
  • Statistical Analysis
  • Time Series Analysis
  • Data Analysis
  • Economics
  • Microeconomics
  • Stata
  • Econometrics
  • Data Modeling
  • Forecasting
  • Data Science Consultation
  • Statistics
Noor Uddin A.

Arlington, Texas

$12/hr
5.0
10 jobs

Hi, I`m Noor ๐Ÿ‘‹ "I turn raw data into clear, actionable insights that empower better decisions and drive real results, every step of the way." I'm a Data Scientist and AI Engineer. Over the past 5+ years, Iโ€™ve worked on projects that combine data engineering, machine learning, and large language models to build intelligent, production-ready solutions. I specialize in designing end-to-end ML pipelines, developing LLM-powered applications (RAG, LangChain, Llama-2/3, OpenAI), and deploying scalable systems on Azure, Databricks, and Docker. My work often involves automating data workflows, improving prediction accuracy, and transforming complex data into clear insights. Some of my favorite projects include building an AI chatbot for e-commerce, a predictive system for event planning, and an IoT protocol translator using LLMs. I value clarity, efficiency, and collaboration and I always aim to deliver results that make a measurable impact. If youโ€™re looking for someone who can turn your data or AI idea into a working solution, Iโ€™d be happy to help.

  • MLOps
  • ML Automation
  • n8n
  • Data Engineering
  • Data Analysis
  • Big Data
  • Azure Machine Learning
  • Databricks Platform
  • Large Language Model
  • Retrieval Augmented Generation
  • Vector Database
  • Web Development
  • MEAN Stack
  • MERN Stack
  • React
  • AI Instruction
  • Technology Tutoring
  • Teaching
Tomas C.

San Martin de los Andes, Argentina

$70/hr
4.9
87 jobs

๐Ÿ† Top Rated Plus ๐ŸŒŸ 100% Job Success ๐Ÿค Satisfied Clients โฑ Quick Turnaround ๐Ÿ“ž Clear Communication Why work with me? Proven Experience: ๐Ÿ’Ž Backed by 15+ years of delivering results through scalable, cost-efficient data solutions. Technical Expertise: ๐Ÿ’Ž AI-Data Architecture: I deliver real-world-ready data through automated, reliable pipelines. The new AI era requires a new data platform. ๐Ÿ’Ž Conversational Analytics & AI Agents: Enable users to chat with their data through AI-driven interfaces. Google Conversational Analytics API and Gemini Enterprise ๐Ÿ’Ž Data Visualization: Skilled in Looker, Looker Studio, Power BI, Tableau, Superset, and others. ๐Ÿ’Ž Data Web Portals: Skilled in developing custom embeddable solutions and full web platforms under your own brand and domain. ๐Ÿ’Ž Database Management: Expertise in SQL (BigQuery, SQL Server, Oracle, MySQL, PostgreSQL, Snowflake) and NoSQL systems. ๐Ÿ’Ž ETL: Experience with both streaming and batch pipelines using Airflow, Apache Beam, Kafka, Debezium, Pub/Sub, and others. ๐Ÿ’Ž Data Modeling: Proficient with dbt, Dataform, and PySpark. ๐Ÿ’Ž Version Control: Comfortable with Git-based tools (GitHub, Bitbucket, GitLab, Azure DevOps). ๐Ÿ’Ž Cloud Platforms: Certified and experienced in GCP, AWS, and Azure. ๐Ÿ’Ž Unstructured Data: JSON, XML, Excel, Google Sheets. ๐Ÿ’Ž GA4 Data: Google Analytics 4 for advanced analysis. Soft Skills & Work Ethic: ๐Ÿ’Ž Versatile & Adaptive: Quick to learn new tools, roles, and business domains. ๐Ÿ’Ž Value-Driven: Focused on delivering high-impact outcomes with cost-efficiency. ๐Ÿ’Ž Detail-Oriented: Committed to precision and quality in every task. ๐Ÿ’Ž Reliable & Time-Conscious: Consistent delivery of high-quality work on time. ๐Ÿ’Ž Leadership: Capable of guiding teams and leading initiatives when needed. ๐Ÿ’Ž Analytical: Skilled at breaking down complex problems and finding effective solutions. ๐Ÿ’Ž Collaborative: Strong team player, effective in multidisciplinary environments. Scalable Technical Capacity: Iโ€™m supported by a network of 15+ specialists, including Solution and Data Architects, Developers, Designers, Process Specialists, DevOps Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, and more. We work collaboratively to ensure your project receives the strongest possible technical support, from strategy to execution. How I approach projects: - Kick-off meeting to review requirements and deliverables - Action plan development using a project management tool - Weekly demo meetings to showcase progress - Detailed time and task tracking - Continuous feedback loop to ensure alignment and improvement - Complete documentation of the solution

  • Data Science
  • Looker Studio
  • Google Sheets
  • SQL
  • Data Visualization
  • Microsoft Power BI
  • BigQuery
  • Data Modeling
  • Data Engineering
  • Google Analytics 4
  • Snowflake
  • Data Analysis
  • Data Analytics
  • AI Data Analytics
  • Dashboard
Djellab A.

Montreal, Canada

$41/hr
4.9
29 jobs

I build AI agents, automations, and RAG systems that ship to production - not demos that die in a notebook. As the founder of BeautyBuzz AI (a live SaaS with real users), I've taken AI products through the full cycle: idea โ†’ build โ†’ deploy โ†’ scale. I'm a full-stack developer with deep AI expertise, which means you get one person who can design the model, build the backend, and ship the app - no handoffs, no gaps. What I build for clients: โ€ข AI Agents & Multi-Agent Systems โ€” LangChain, LangGraph, CrewAI; tool-calling, memory, orchestration โ€ข AI Automation & Workflows โ€” n8n, Make, Zapier + OpenAI/Claude; connect your CRM, email, Slack, docs so work runs itself โ€ข RAG & Knowledge Assistants โ€” chat over your documents/data with accurate, cited answers (vector DBs, hybrid retrieval) โ€ข LLM Fine-Tuning & Integration โ€” OpenAI, Anthropic Claude, Gemini, Llama; prompt engineering, evals, cost/latency optimization โ€ข Full-Stack AI Products & MVPs โ€” Python/FastAPI backends, clean databases, cloud deployment (AWS/GCP/Azure), Docker, CI/CD Why clients hire me: โœ… 100% Job Success Score and $50K+ earned on Upwork โœ… Founder of a real, deployed AI SaaS โ€” I think about your business outcome, not just the code โœ… Recent 5-star work: agentic RAG systems, document-processing automation, a high-performance LLM inference engine, and a 150-hour PostgreSQL + Python app Tech I work with daily: Python, FastAPI, LangChain, LangGraph, OpenAI & Claude APIs, MCP, Pinecone/pgvector, Hugging Face, PyTorch, TensorFlow, Docker, AWS, n8n, SQL, React/Next.js. If you need an AI agent, an automation that saves hours every week, or a production-ready AI feature built properly the first time, send me a message or invite me to your job - I reply within hours and I'll tell you honestly what's worth building.

  • Data Science
  • Python
  • Recommendation System
  • Natural Language Processing
  • Deep Learning
  • Computer Vision
  • Artificial Intelligence
  • Machine Learning
  • AI Agent Development
  • AI App Development
  • LangChain
  • Retrieval Augmented Generation
  • Large Language Model
  • Generative AI
  • AI Chatbot
  • Automation
  • OpenAI API
  • Claude
  • FastAPI
  • PostgreSQL

How it works

Post a job for free Post a job

Tell us what you need. Create your own job post or generate one with AI then filter talent matches.

Hire top talent fast

Consult, interview, and hire quickly, so you can meet the freelancers you're excited about.

Collaborate easily

Use Upwork to chat or video call, share files, and track project progress right from the app.

Payment simplified

Manage payments in one place with flexible billing options. Only pay for approved work, hourly or by milestone.

Don't just take our word for it

Resources to help you hire

Cost to hire a Data Scientist

Cost to hire a Data Scientist

Explore typical Data Scientist rates and what businesses pay to hire top talent.

Data Scientist job description template

Data Scientist job description template

Get tips to write a job post that attracts qualified Data Scientists.

Data Scientist interview questions

Data Scientist interview questions

Top interview questions to help you hire the right Data Scientists, faster.

Data scientist hiring guide

Data scientists turn raw data into strategic insights that drive business decisions. Whether you need to build predictive models, optimize operations, or uncover customer patterns, hiring the right data scientist can transform how your organization uses data.

What does a data scientist do?

A data scientist analyzes complex datasets to extract actionable insights that drive business decisions. They combine statistical expertise, programming skills, and domain knowledge to turn raw data into strategic advantages.

Key responsibilities include:

  • Data collection and preparation. Gathering data from multiple sources such as internal databases, third-party APIs, and web scraping. They spend significant time cleaning datasets to prevent garbage-in, garbage-out scenarios.

  • Exploratory analysis. Using statistical methods to identify patterns, trends, and relationships in data.

  • Predictive modeling. Building machine learning models that forecast outcomes like customer behavior, sales trends, or operational risks.

  • Machine learning deployment. Developing and deploying algorithms for tasks like recommendation systems, fraud detection, or process automation.

  • Data visualization. Creating dashboards and reports that make insights accessible to executives, using tools like Tableau, Power BI, or Matplotlib.

  • Experimentation. Designing and analyzing A/B tests to validate hypotheses and guide product decisions.

How to hire a data scientist on Upwork

Upwork makes it easy to find and hire freelance data scientists, with many skilled candidates available to meet your timeline and budget needs. To streamline your hiring process, just follow these four simple steps.

Step 1: Craft a targeted job post

A well-crafted job post attracts data scientists with the specific expertise your project requires. In your post:

  • Describe your business problem and expected deliverables (i.e., building predictive models or dashboards, boosting sales or reducing costs)

  • List required technical skills like Python, SQL, or TensorFlow

  • Give a realistic range for required experience relative to your budget

To create a tailored job post quickly, try the Job Post Generator powered by Umaโ„ข, Upworkโ€™s Mindful AI. Describe what you need in a few sentences, and Uma will craft a job post in seconds. You can also review data scientist job description templates for ideas and inspiration.

Step 2: Filter and evaluate proposals

Taking a structured approach to reviewing proposals will help you move efficiently from a large applicant pool to a focused shortlist.

  • Have Uma give instant video interviews and side-by-side comparisons

  • Use Upworkโ€™s filters to find candidates by rate, location, and experience

  • Review proposals for signs that the candidate has understood your job post and has the skills to meet your needs

  • Review portfolios for past projects and case studies that show measurable results

Step 3: Interview your top choices

Quick video interviews give you the chance to ask any questions you have left for your top candidates, and to get a feel for what a collaboration with them might be like.

  • Schedule and conduct interviews within Upwork messaging to get instant transcripts and summaries from Uma

  • Ask the candidates to walk you through past work from their portfolio, focusing on aspects that are similar to your project and challenges they overcame

  • Discuss their process for data collection and cleaning, and other processes relevant to your project

  • Have them walk you through what overfitting might look like, and how they handle missing data in a dataset

  • Cover key soft skills, such as how they present complex topics to non-technical stakeholders

To help you prepare for the interviews, especially if you arenโ€™t technically minded, consider reviewing data scientist interview questions.

Step 4: Agree on scope and begin work

Once youโ€™ve found the right person, you can send a contract directly through the Upwork marketplace. A solid contract protects both parties and helps collaborations be successful from beginning to end.

  • Use Upwork's contract workroom, messaging, and payment protection for secure collaboration

  • Choose fixed-price contracts for projects with clear deliverables, such as a single dataset analysis and summary

  • Break large projects into milestones, such as data collection, cleaning and processing, ML model training, model validation, and deployment 

  • Choose hourly contracts for ongoing work or projects without clear deliverables, such as ML model monitoring, retraining, and fine tuning

Upwork is not affiliated with and does not sponsor or endorse any of the tools or services discussed in this article. These tools and services are provided only as potential options, and each reader and company should take the time needed to adequately analyze and determine the tools or services that would best fit their specific needs and situation.

The rates and information provided in this article are based on current data and industry sources available at the time of publication. Freelance rates can vary depending on factors such as experience, location, project scope, and market conditions. Readers are encouraged to conduct their own research to confirm current rates and trends, as this information may change over time.

How much does hiring a data scientist cost?

Independent data scientists on Upwork charge prices ranging from $35-$250 per hour. Your exact cost will depend on the scope and complexity of the project, as well as the skills and experience of the professional. The following chart lists typical costs for data science projects often found through Upwork.

Data analysis and reporting

$1,500-$5,000 /project

Entry- to mid-level
  • Single dataset analysis and statistical summary
  • Basic visualizations
  • Insights report with recommendations

Predictive model development

$5,000-$15,000 /project

Mid- to senior-level
  • Custom ML model design and training
  • Validation and accuracy testing
  • Deployment guide

End-to-end data science solution

$15,000+ /project

Senior-level or specialist
  • Complete data pipeline setup
  • Multiple model development
  • System integration and training

Ongoing analytics support

$4,000-$15,000 /month

Mid- to senior-level
  • Monthly KPI dashboards
  • Model performance monitoring
  • Ad hoc analysis and improvement

Strategic data science consulting

$10,000-$30,000+ /project

Expert or executive-level
  • Data maturity assessment
  • ML roadmap development
  • Team capability building

FAQs about data scientists

Frequently asked questions

Is hiring a data scientist worth it?

Hiring a data scientist is worth it when you have meaningful data and business questions requiring specialized analysis. They can optimize pricing strategies, predict customer churn, identify operational inefficiencies, and uncover revenue opportunities that would otherwise remain hidden.

What skills should I look for when hiring a data scientist?

Essential technical skills include proficiency in programming languages (Python, R, SQL), statistical analysis, machine learning frameworks (TensorFlow, scikit-learn, PyTorch), and data visualization tools (Tableau, Power BI).

Beyond technical abilities, look for strong problem-solving skills, business acumen, and clear communication to explain findings to non-technical stakeholders.

What is the difference between a data analyst and a data scientist?

A data analyst focuses on descriptive work โ€” understanding what happened through reports and dashboards. A data scientist builds predictive machine learning models to forecast what will happen and recommend actions. If historical analysis fits your needs, consider hiring a data analyst. Read more about comparing the two roles.

What's the difference between a data scientist and a machine learning engineer?

A data scientist explores data and builds prototype models. A machine learning engineer deploys those models into production applications at scale, focusing on software engineering and system infrastructure. If you need production deployment, consider hiring a machine learning engineer. Read more to compare the two roles.

How can a data scientist add value to my business?

A data scientist adds value by solving specific business problems with data-driven approaches. Common value-adds include increasing revenue through recommendation systems, reducing costs with predictive maintenance, and improving customer experience through segmentation.

How do I evaluate a data scientist's work quality?

For technical quality, review model performance metrics (accuracy, precision, recall), assess methodology documentation, and verify code reproducibility. For business impact, determine if findings are actionable and assess how clearly they communicate results. On Upwork, set project milestones to review work incrementally.