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Data et analytics

Data Scientist - poste à distance

AffirmedRx, PBC

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Publiée : (il y a 21 jours)Active : jusqu'au 2 octobre 2026

Data Scientist - Data et analytics, à distance

L'entreprise AffirmedRx, PBC recrute : Data Scientist. Le poste relève de la catégorie Data et analytics et se fait entièrement à distance. Aucune restriction n'est posée sur le lieu de résidence du candidat, vous pouvez donc postuler de partout.

L'annonce met en avant Machine Learning : c'est l'expérience de cet outil précis qui fera la différence.

L'entreprise n'a publié aucun chiffre, cela se règle en entretien. L'annonce ne pose aucune condition d'horaires.

Cette offre a passé un contrôle automatique : les annonces qui exigent un permis de travail étranger, un parrainage de visa, une nationalité précise ou une résidence dans un pays nommé n'entrent pas dans la liste.

En bref

Entreprise
AffirmedRx, PBC
Catégorie
Data et analytics
Qui peut postuler
De n'importe quel pays du monde
Mode de travail
Entièrement à distance
Outils
Machine Learning
Type de contrat
Temps plein
Publiée
3 août 2026 (il y a 21 jours)
Validité
jusqu'au 2 octobre 2026
Origine
Himalayas

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La description de l'entreprise

AffirmedRx is on a mission to improve health care outcomes by bringing clarity, integrity, and trust to pharmacy benefit management. We are committed to making pharmacy benefits easy to understand, straightforward to access and always in the best interest of employers and the lives they impact. We accomplish this by bringing total clarity to business practices, leading with clinical approaches, and utilizing state-of-the-art technology. Join us in improving health care outcomes for all! We promise to do what’s right, always. Position Summary: The Data Scientist (AI/ML) designs, builds, and validates the advanced analytics that turn pharmacy, claims, clinical, and member data into decisions. This is a hands-on modeling role: the person owns machine learning models end to end, applies AI and natural language processing to unstructured clinical and member data, resolves member identity across fragmented data sources, and packages results into tools and dashboards the business can use. The role sits at the intersection of data science, clinical/pharmacy reporting, and applied AI, and partners closely with data engineering, clinical, reporting, and client-success teams. What you will do: Machine Learning and Predictive Modeling:

* Build predictive and prescriptive ML models for pharmacy cost and risk (e.g., forecasting second-year member spend), including feature engineering, model selection, and explainability analysis (e.g., SHAP-based feature attribution)

* Develop member-level risk and comorbidity scoring, mapping drug identifiers (NDC → ATC) to clinical conditions and severity weights, and validating outputs against edge cases

* Apply ML to automate high-effort clinical operations processes (e.g., prior-authorization override automation), moving manual workflows into rules-based and model-driven pipelines

Applied AI and Natural Language Processing:

* Use AI/NLP to analyze unstructured member and clinical text - sentiment analysis, topic modeling, and tokenization of open-ended survey and feedback data

* Apply AI tooling (LLMs / copilots and internal AI services) to automate clinical policy and documentation workflows, including prompt design, output validation, and controls against hallucination and format drift

* Contribute to the organization’s broader AI direction: evaluating models, defining evaluation/answer-key datasets, and building drift and validation checks for AI outputs

Member Identity Resolution and Data Quality:

* Design and maintain probabilistic (fuzzy) matching logic to assign and reconcile unique member identifiers across carriers and source systems, including collision handling, cluster analysis, and audit/logging frameworks

* Monitor and improve match rates, investigate false positives and fragmentation, and document data lineage and safeguards against duplicates

Clinical and Pharmacy Analytics:

* Produce clinical and pharmacy analytics such as medication adherence and persistence (drug-, class-, and NDC-level), aligned to compliance requirements (e.g., URAC / PQA measures)

* QA and validate reporting products (e.g., pharmacy trend dashboards, PMPM metrics), reconciling data-point discrepancies across source systems

Analytical Tooling and Delivery:

* Build analytical tools and prototypes (e.g., formulary/tier decision tools and cost-comparison tools), including lightweight front ends (e.g., Streamlit) for sales, clinical, and pricing use

* Deliver validated datasets and tables into the data warehouse in partnership with data engineering, and support the transition of prototypes into production

Validation, Documentation, and Collaboration:

* Own QA and validation for analytical outputs, including auditing of claims files and validation of model results before release

* Document models, logic, data sources, schedules, and troubleshooting steps to make work reproducible and auditable

* Collaborate across clinical, reporting, pricing, client-success, and engineering stakeholders to gather requirements and translate them into analytical specifications

What you need:

* Degree in a quantitative field (data science, statistics, computer science, applied math) or equivalent experience

* 2-3 years of experience using Python and SQL for data analysis, machine learning, NLP, data quality, and record-matching solutions. Data modeling experience in PBM and/or healthcare industry in general preferred

* Strong Python for data science and ML (e.g., pandas plus a modeling stack), and proficiency in SQL

* Demonstrated experience building and validating ML models, including feature engineering and model explainability

* Experience with NLP techniques (sentiment analysis, topic modeling) and with applying AI/LLM tooling to real workflows, including output validation

* Experience with entity resolution / probabilistic record matching and data-quality analysis

* Comfort working with a modern cloud data warehouse and data lake, and partnering with data engineering on production hand-off

* Healthcare, pharmacy benefit management (PBM), or claims-data experience

* Familiarity with pharmacy data concepts (NDC, GPI, ATC, formulary tiers, prior authorization, rebates)

* Experience with compliance-driven reporting (e.g., URAC / PQA measures)

* Experience building analytical front ends or dashboards (e.g., Streamlit, BI tools) for non-technical stakeholders

* Willingness and ability to travel (10%-20%)

What you get:

* To impact industry change in the pharmacy benefits management space, while delivering the highest quality patient outcomes

* To work in a culture where people thrive because when OUR team thrives, OUR business thrives

* Competitive compensation, including health, dental, vision and other benefits

Note: AffirmedRx is committed to providing equal employment opportunities to all employees and applicants for employment. Remote employees are expected to maintain a professional work environment free of distractions to ensure optimal performance and collaboration. Originally posted on Himalayas

Le texte est conservé dans la langue d'origine de l'entreprise, car c'est dans cette langue que vous postulerez.

Cette offre a été publiée sur Himalayas. Annonce d'origine (Himalayas)

Questions fréquentes sur cette offre

Puis-je postuler au poste de Data Scientist depuis là où je vis ?

Oui. Pour cette offre, AffirmedRx, PBC accepte des candidats de n'importe quel pays du monde, vous n'avez donc besoin d'aucun permis de travail pour un autre pays. L'annonce a passé un contrôle automatique : si l'entreprise avait exigé un permis de travail, un parrainage de visa ou une résidence dans un pays précis, elle ne figurerait pas sur ce tableau.

Quelle rémunération est indiquée ?

Pour cette offre, AffirmedRx, PBC n'a publié aucune rémunération. La plupart des annonces à distance ne donnent aucun chiffre, cela se règle en entretien.

Comment postuler ?

Vous postulez directement auprès de l'entreprise, via l'annonce d'origine publiée sur Himalayas. Donator ne reçoit aucune candidature, ne prend aucune commission et ne conserve aucun CV.

De quel type d'offre s'agit-il ?

Un poste entièrement à distance dans la catégorie Data et analytics. Les annonces hybrides et tout ce qui impose une présence au bureau ne sont pas publiés sur ce tableau.

Certificats gratuits pour cette offre

Cette annonce demande Machine Learning. Vous trouverez ci-dessous les attestations gratuites qui couvrent précisément ces outils.

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