Senior Data Scientist, Business Intelligence Team
hace 4 semanas
**Company Description** Welcome to the good side of tech**
You might have heard about us, but with a different name**:Doctoralia.** It all started 10 years ago, when we asked ourselves: is anyone in healthcare thinking about patients? We jumped in and we empowered patients by giving them access to **leave and read reviews about their visit.** We then provided doctors with the technology to **manage bookings easily and save time,** so they could devote themselves to what they always wanted: treating patients. And today is the day in which we ask you: wanna join us in the next step of making the healthcare experience more human?
**Docplanner at scale**
We are leaders in **13 countries** so far, and more than **90 million patients** trust us every month. **130.000 specialists** believe in us and our product, and so do **leading venture capital funds **such as Point Nine Capital, Goldman Sachs Asset Management and One Peak Partners. And yet, employing over 2.500 people all over the globe, we managed to keep the startup-mindset we started with over 10 years ago.
**How does Docplanner Tech fit here?**
At Docplanner Tech we are a diverse group of over 400 people working in Engineering, Data, and Product teams. We are responsible for building the product for all locations. Many of us have been here for over 5 years, yet we still welcome each new person with great joy and excitement.
We could tell you about us, but we will let our reviews on Glassdoor speak for themselves. In case you’d like to see how it feels to be 100% yourself at work, here’s a video of us.
**And why should you join us?**
Because it feels good to tell your family and your friends how you made the world a little bit better. You go to bed **knowing that what you do matters, and that your talents align with your beliefs.**
We want to make the healthcare experience more human, and that starts with you being you. We believe that taking the diversity of human experience into account makes a better healthcare experience for all. We’re not just different: we embrace diversity. We will encourage you to come to work your whole self, and that includes not coming to the office at all if you prefer not to, as we're 100% remote-friendly.
In this role as a **Senior Data Scientist** at Docplanner, your main focus will be unlocking actionable insights for our senior leadership and operations, with particular emphasis on Sales excellence. You will take ownership of our high-impact Decision Science initiatives, leveraging our large-scale data sources and ML infrastructure, while collaborating closely with cross-functional team members, including business stakeholders and data engineers.
**How would you be impacting our mission?**
- Lead the complete model development lifecycle, implementing best practices for consistent testing and efficient software delivery.
- Create, deploy, and fine-tune predictive models and machine learning algorithms for specific use cases, including developing ML models to interpret data, recognize patterns, and forecast outcomes.
- Craft rigorous experiments and deliver insights to answer empirical questions.
- Collaborate with data engineering and infrastructure teams to maintain and enhance a centralized data platform.
- Participate in interdisciplinary projects at the intersection of business and technology, utilizing opportunities to develop innovative solutions that provide substantial value to customers on a large scale.
- Document workflows, model specifics, and software solutions to facilitate knowledge sharing and ensure reproducibility.
**Qualifications** What will help you thrive?**
- 5+ years of relevant experience in data, working with state-of-the-art technologies.
- Good understanding of statistical models (hypothesis testing, regression analysis, etc.) and time series analysis
- Expertise in ML-based methodologies, both supervised and unsupervised (regression, tree models, etc.), and model evaluation techniques.
- Hands-on experience in model development, deployment, and optimization using libraries and frameworks like NumPy, Pandas, Scikit-learn, PyTorch, and Keras.
- Experience working with Data Warehouses such as Redshift, BigQuery, and Snowflake, and familiarity with version control practices using Git.
- Understanding of model development lifecycle, MLOps, containerization and orchestration: Docker, Kubernetes, MLFlow, etc.
- Excellent communication skills and stakeholder management, with the ability to convey complex methodologies and data insights clearly to both technical and non-technical audiences.
- Strong ability to translate business needs into technical requirements, including feature engineering and model fine-tuning, with a pragmatic approach to problem-solving.
- Agile mindset with the capability to experiment, test hypotheses, and adapt to a constantly evolving work environment, alongside a commitment to continuous learning and big-picture thinking.
- Growth mindset: While we don't expec
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