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Click "Post a job". You can post one job a month for free: it stays open 14 days and is reviewed first if your company website is not verified. Paid plans cover more jobs. The key is to describe the business problem, not just the title: are you solving a churn problem, building a forecasting model, or setting up an experimentation framework? That context attracts data scientists with the right background. Add your data stack (SQL, BigQuery, Snowflake, dbt), the expected deliverables, and a compensation range. Job posts with a salary range consistently attract more senior candidates. Then publish: the job goes live right away, or after a review if your company website is not verified.

The talent section on this page is pre-filtered for data scientists and analytics specialists. Browse profiles showing headline, core skills, and an experience summary. Click any profile for the full view: work history, projects, tools used, and their approach to analytical problems. Filter by experience level and availability. For data science roles specifically, prioritize profiles that describe business outcomes — "improved forecast accuracy by 18%", "reduced CAC by 22%" — over those that only list tools. Outcome-oriented profiles signal candidates who work with business context, not just data for its own sake.

Python, R, SQL, PySpark, Pandas, NumPy, scikit-learn, Statsmodels, Tableau, Power BI, Looker, dbt, Snowflake, BigQuery, Databricks, A/B testing, statistical inference, survival analysis, time-series forecasting (ARIMA, Prophet, NeuralProphet), Bayesian modeling, and causal inference. On the applied ML side: classification, regression, clustering, anomaly detection, and recommendation systems. Specify which skills are required versus preferred — data science is broad, and candidates tailor their application based on what problems they will actually be solving.

Yes, one job a month is free, with no credit card. It stays open 14 days and is reviewed first if your company website is not verified. Paid plans cover more jobs, and you can also post a single job for $99 without an account. There is no placement fee when you hire.

It depends on the role and on how specific the job post is, so we do not promise a delay. Strong candidates tend to pass on vague postings that do not explain what problem they would be solving. A clear description of the business context, the data environment, and the expected impact of the role is the single most effective way to get high-quality data science applications quickly. A stated compensation range further accelerates the process.

Yes. New profiles are checked by our team before they are listed: a real name, a real description of the person's work and, if there is a photo, their own face. Gibberish or copy-pasted profiles are not shown. Skills are not tested, so use profiles to shortlist on domain fit, then check skills with a case study or a live analytical session.

Yes. RemoteAI has data scientists across all seniority levels. Entry-level analysts (1–2 years) are strong on SQL, visualization, and exploratory analysis — ideal for companies that need strong data fundamentals before adding ML complexity. Mid-level data scientists (3–5 years) can own a modeling problem end-to-end. Senior data scientists (5–10 years) define the analytical strategy, mentor others, and drive experimentation frameworks. Principal and head-of-data profiles (10+ years) are strategic hires. Specify the seniority level and the autonomy expected in your post — it is the most effective way to attract the right applications.

The strongest data science job posts on RemoteAI describe a real business problem in plain language, specify the data environment honestly, and set clear expectations for deliverables. Instead of "must have strong ML skills", write "building a weekly demand forecast for 50K SKUs — we use BigQuery, dbt, and Python, and the role owns the forecasting pipeline end-to-end." That level of specificity tells experienced candidates what the role actually involves, whether their background matches, and whether the team is set up to do real data science — all signals that attract senior candidates and filter out junior ones who are over-applying.

Yes. RemoteAI has data scientists from India, the US, UK, Canada, Europe, Brazil, and many other countries; many have worked in remote teams. Many have worked across multiple timezones and are comfortable with async documentation, written communication, and distributed team norms. If timezone overlap matters — for example, daily standups at 9am EST — specify the required overlap hours in your post. Candidates confirm availability before applying, which means your interview pipeline only includes engineers who can actually work your schedule.

Free plan: you create a company account and read applications in your RemoteAI dashboard, with messaging and AI matching. One job a month, open 14 days, reviewed first if your website is not verified. The $99 option: no account and no dashboard. Candidates apply to your own email or link, and the listing is reviewed before it goes live.