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Senior Data Scientist (Remote Friendly)

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Published
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17 Oct 2026Apply before
Opportunity details

About this role.

AI Summary

Docplanner is seeking a Senior Data Scientist to deliver end-to-end analytics, business intelligence, experimentation, and machine-learning initiatives across its global healthcare platform. The role combines exploratory analysis, predictive modeling, A/B testing, production deployment, and model monitoring using large-scale datasets and modern ML infrastructure. The successful candidate will partner with Product, Sales, Marketing, Operations, Engineering, and analytics stakeholders to translate business needs into measurable outcomes. Strong Python, SQL, statistics, cloud data warehouse, MLOps, and cross-functional communication capabilities are central to the position.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior, high-impact role requiring ownership from ambiguous problem definition through production deployment and monitoring. It demands both deep ML and experimentation expertise and the ability to influence varied business and technical stakeholders in a fast-paced international environment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$165,000
US market range$140k–$200k
AI insightNo salary was disclosed, so these are estimated annual US-market base-salary figures in USD for a Senior Data Scientist with 5+ years of experience and production ML/MLOps responsibilities. Actual compensation may vary materially by country, local employment arrangement, bonus, and equity.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe an end-to-end machine-learning project you delivered from problem definition through production monitoring.

I would begin by aligning on the business decision, success metric, constraints, and baseline. After validating data quality and developing an appropriately simple model, I would evaluate offline performance and business impact, deploy through a reproducible pipeline, and monitor model quality, drift, reliability, and outcome metrics.

How would you design an A/B test to assess a product or operational change?

I would define the primary metric and guardrails, formulate the hypothesis, determine the unit of randomization, estimate sample size and duration, and check for segmentation or interference risks. I would predefine the analysis plan, validate experiment integrity during execution, and communicate both statistical and practical significance with clear recommendations.

How do you translate an ambiguous stakeholder request into a data-science solution?

I first clarify the underlying decision, target users, expected business value, available data, timeline, and definition of success. I then propose a phased approach, often starting with exploratory analysis or a lightweight baseline, so stakeholders can validate value before investing in a more complex production solution.

What practices would you use to make an ML workflow scalable and maintainable?

I would version code, data assumptions, experiments, and models; use automated testing and CI/CD; containerize reproducible workloads; and maintain clear documentation. Tools such as Git, Docker, MLflow, orchestration pipelines, and monitoring help ensure models can be reliably deployed, audited, and improved.

How would you evaluate whether an AI agent or copilot genuinely improves a data-science workflow?

I would identify a specific workflow bottleneck and establish baseline measures such as cycle time, error rate, review burden, and output quality. I would test the tool with appropriate human review and security controls, then retain it only if it produces measurable productivity gains without reducing analytical rigor, privacy, or reproducibility.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

Company Description

At Docplanner Group, we’re on a mission to help people live longer, healthier lives. As the world’s largest healthcare platform, each month, we connect 24 million patients with 280k doctors across 13 countries (through brands like ZnanyLekarz, Doctoralia, MioDottore, DoktorTakvimi, and jameda). Our marketplaces, SaaS and AI tools simplify daily tasks and help doctors, clinics and hospitals work more efficiently, so they can focus on what really matters: caring for their patients.

Learn more about our products here: pro.doctoralia.es

Why join us?

📊 Real impact – We help doctors help patients. Your work truly makes a difference.

📈 At scale, yet agile – 3,000+ employees, but still fast, flexible, and hands-on.

✨ Shape the future, sustain growth – Make a difference now and build for long-term success.

Job Description

As a Senior Data Scientist at Docplanner, you will help transform complex data into actionable insights and scalable machine learning solutions that directly impact business growth and operational excellence. You will work on high-impact initiatives across Business, Operations, and Product areas, partnering closely with business stakeholders, engineers, and analytics teams.

You will own data science and BI projects end-to-end – from problem definition and experimentation to model deployment and monitoring – using large-scale datasets and ML infrastructure. We are looking for someone who combines strong technical expertise with business understanding and a pragmatic, impact-driven mindset.

This role is part of our Global Data department, supporting data and AI initiatives across Docplanner’s international operations.

How would you be impacting our mission?

  • Own and deliver end-to-end data science and BI projects, from exploration and experimentation to deployment in production.

  • Build predictive models and machine learning solutions that support business decision-making and operational efficiency.

  • Analyze large datasets to uncover actionable insights, trends, and growth opportunities.

  • Design and evaluate experiments and A/B tests to measure impact and validate hypotheses.

  • Collaborate with cross-functional teams across Product, Sales, Marketing, and Engineering.

  • Improve and maintain scalable data pipelines and ML workflows together with Data & ML engineering teams.

  • Use modern AI tools, copilots, and AI agents to automate workflows, accelerate experimentation, and improve productivity.

  • Contribute to best practices in model development, testing, deployment, and documentation.

What will help you thrive?

  • 5+ years of experience in Data Science, Machine Learning, or Advanced Analytics roles.

  • Strong Python skills and hands-on experience with libraries such as Pandas, Scikit-learn, TensorFlow, or PyTorch.

  • Solid understanding of statistics, experimentation, machine learning, and model evaluation techniques.

  • Experience working with large datasets, SQL, and data warehouses such as Redshift, BigQuery, or Snowflake.

  • Familiarity with MLOps and modern development practices (Git, Docker, MLflow, CI/CD).

  • Experience using AI-powered tools or AI agents to improve efficiency and automate repetitive tasks.

  • Strong communication skills and ability to translate business needs into practical technical solutions.

  • Comfortable working in agile, fast-paced, and cross-functional environments.

Bonus points

  • Experience with Airflow, k8s, Jupyter Notebook, Athena, or other big data technologies.

  • Experience with NLP, LLMs, or AI agent workflows.

  • Familiarity with BI and visualization tools such as Tableau or Superset.

  • Previous experience in SaaS or high-growth tech environments.

What to Expect from Our Hiring Process

We like to keep things transparent and efficient! Here’s what the process usually looks like (though it might vary slightly depending on the role):

1️⃣ Intro Chat – A first call with our Talent Partner Giuliana to explore mutual fit around relevant skills, value alignment, and motivation.

2️⃣Hiring Manager Interview – A deeper conversation about your background, aspirations, and experience with Wiktor, Business Intelligence Manager and your potential manager in this role. Take this chance to ask anything on your mind—it’s just as much about making sure we’re the right fit for you, too.

3️⃣Business Case – A take-home exercise incl. a few days’ preparation time, designed to understand how you approach real-life problems. You’ll then walk us through your approach in a collaborative discussion with the hiring manager and the team to discuss your thoughts and findings.

4️⃣Final Interview – A final conversation with one of your main stakeholder from our Global Team.

5️⃣ References & Offer!

Why You’ll Love It Here

💙 Global Benefits – No matter where you are, you’ll have access to:

  • Healthcare insurance – so you can focus on what matters.

  • Wellness that works for you – from gym memberships to mental health support, we’ve got you covered.

  • Time off that counts – whether it’s a vacation, your birthday, or just a day to recharge, we believe in balance.

📍 Local Perks – Depending on your location, you will be entitled to local benefits like meal vouchers (ticket restaurant), transport allowances, or extended parental leave.

🚀 Career Growth – We’re growing, and so can you! You’ll find lots of chances to learn, develop, and explore new paths—whether within your team or through cross-functional projects.

🌎 A Truly Global Team – Work with talented people from all over the world in a diverse and inclusive environment.

⏳ Flexibility That Works for You – Remote work and flexible hours aren’t just buzzwords here. While the extent of flexibility depends on your role and team, we value results over rigid schedules. Prefer an office setting? You’re welcome at any of our hubs in Barcelona, Warsaw, Curitiba, Rio de Janeiro, Mexico City, Bogotá, Munich, Rome or Bologna.

Please note: At this time, we are not able to sponsor visas for this position. To apply, you must already have the legal right to work in your country of residence or the location of the role.

What We Believe In

At Docplanner, our values guide everything we do:

📊 Focus on results – we’re here to make an impact.

🧠 Think like an owner – take responsibility, drive outcomes.

✂️ Keep it simple, keep it lean – smart solutions over complexity.

🔊 Be respectful and radically honest – openness builds trust.

📚 Learn and be curious – growth is part of the job.

Don’t just take our word for it—check out our Glassdoor to hear what our people say!

_________________________________________________________________________

We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. We welcome applicants from all walks of life, regardless of gender, disability, or background, and are dedicated to fostering an inclusive workplace where everyone feels valued and empowered to contribute.

Apply now >

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