Senior Data Scientist at Kalderos

Valencia, Valencian Community, Spain

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Logistics, Supply ChainIndustries

Requirements

Master’s in a quantitative field (Computer Science, Statistics, Mathematics, Operations Research, Engineering) or equivalent experience. PhD is a plus
6+ years of professional experience in data science/ML, including delivering models to production and measuring business impact
Deep knowledge of statistics, data modeling, machine learning, and visualization; practical experience applying reinforcement learning concepts to real-world decision-making
Strong proficiency in Python and a deep learning framework (PyTorch or TensorFlow); solid SQL and data wrangling skills
Proven experience with experiment design, hypothesis testing, and model diagnostics; ability to build clear, decision-focused visualizations
MLOps competence: containers, CI/CD, and deploying models in cloud environments (Azure/AWS/GCP)
Track record of operating production ML systems, including monitoring, alerting, and incident response
Excellent communication, stakeholder management, and the ability to lead cross-functional initiatives with global/distributed teams

Responsibilities

Lead end-to-end ML solution design, translating business objectives into modeling plans, success metrics, and deployment strategies
Architect training and evaluation environments, including simulators, to safely assess model behavior prior to live deployment
Establish data quality standards and build reliable pipelines for ingestion, cleaning, feature engineering, labeling, and experiment tracking
Define rewards, constraints, and safety considerations; plan offline evaluations and controlled experiments to validate performance
Validate and operate production models: define acceptance criteria and test plans, continuously monitor performance/latency/drift, investigate anomalies, and apply corrective measures in partnership with software engineering
Drive responsible AI practices, model governance, documentation standards, and reproducible experimentation throughout the ML lifecycle
Partner with product and engineering to scope initiatives, prioritize roadmaps, and integrate models into scalable services with robust observability
Mentor and coach data scientists; lead technical reviews, elevate code quality, and promote best practices
Communicate findings and recommendations to stakeholders and leadership through clear narratives and visualizations; influence decision-making with data

Skills

Key technologies and capabilities for this role

Machine LearningReinforcement LearningData PipelinesFeature EngineeringModel ValidationProduction DeploymentExperiment TrackingModel MonitoringSimulatorsResponsible AIML Ops

Questions & Answers

Common questions about this position

What education and experience are required for the Senior Data Scientist role?

A Master’s in a quantitative field (Computer Science, Statistics, Mathematics, Operations Research, Engineering) or equivalent experience is required, with PhD preferred. Candidates need 6+ years of professional experience in data science/ML, including delivering models to production and measuring business impact.

What technical skills are essential for this position?

Strong proficiency in Python and a deep learning framework (PyTorch or TensorFlow), solid SQL and data wrangling skills, deep knowledge of statistics, data modeling, machine learning, and MLOps competence including containers, CI/CD, and cloud deployment (Azure/AWS/GCP) are required.

Is remote work an option for this role?

This information is not specified in the job description.

What is the salary or compensation for this position?

This information is not specified in the job description.

What soft skills or experiences make a strong candidate?

Excellent communication, stakeholder management, ability to lead cross-functional initiatives with global/distributed teams, and experience mentoring data scientists are key. A track record of operating production ML systems and driving responsible AI practices also strengthens candidacy.

Kalderos

Optimizes drug discount management platform

About Kalderos

Kalderos provides a platform designed to improve the management of drug discounts in the healthcare sector. This platform helps healthcare providers and pharmaceutical manufacturers accurately manage discount claims and avoid duplicate discounts. By using data analytics and machine learning, Kalderos simplifies the complicated process of drug discount management, making it more efficient and clear. Clients subscribe to the service, paying for access to the platform and its features, which include real-time data validation, detailed reporting tools, and automated compliance checks. These features assist clients in saving time and minimizing financial risks related to drug discount programs. Kalderos primarily serves large healthcare systems and pharmaceutical companies in the United States.

Chicago, IllinoisHeadquarters

2016Year Founded

$48.6MTotal Funding

LATE_VCCompany Stage

Consulting, AI & Machine Learning, HealthcareIndustries

51-200Employees

Benefits

Health Insurance

Dental Insurance

Vision Insurance

401(k) Company Match

401(k) Retirement Plan

Paid Vacation

Phone/Internet Stipend

Commuter Benefits

Home Office Stipend

Risks

Strategic shifts by new CSO Daryl Todd may disrupt existing operations.

Involvement in Arkansas litigation could lead to legal challenges or reputational damage.

Accountant shortage in the U.S. may impact Kalderos' financial reporting capabilities.

Differentiation

Kalderos offers a unique SaaS-based drug discount management solution.

The platform uses machine learning to detect inconsistencies in drug discount claims.

Kalderos provides real-time data validation and automated compliance checks.

Upsides

Growing demand for AI-driven compliance solutions in healthcare boosts Kalderos' market potential.

Expansion of 340B program compliance needs increases demand for Kalderos' services.

Collaboration opportunities with hospitals enhance Kalderos' drug discount management capabilities.

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