Senior Data Scientist - Barcelona, España - AstraZeneca

AstraZeneca
AstraZeneca
Empresa verificada
Barcelona, España

hace 1 mes

Isabel García

Publicado por:

Isabel García

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Descripción
At AstraZeneca, we work together to deliver innovative medicines to patients across global boundaries. We make an impact and find solutions to challenges.

We do this with integrity, even in the most difficult situations, because we are committed to doing the right thing.

The Digital Health R&D Human-centered AI (HAI) Team aims to transform the patient experience and clinical trial process. Our solutions make a difference to the lives of our patients.

Examples of projects the team works on include machine learning models for predicting and monitoring various aspects of clinical trials such as patient recruitment and trial duration, optimization of trial design from site selection to patient experience and much more


Typical Accountabilities

  • Works with complex multimodal clinical datasets. Conducts analysis using data science and machine learning techniques.
  • Builds data and analysis pipelines to deliver clinical insights and reusable capabilities.
  • Researches and implements novel methods in optimization, machine learning, data analysis, data visualization.
  • Communicates results to technical and nontechnical stakeholders at multiple levels.
  • Independently keeps own knowledge up to date and learns from senior team members, proposing appropriate training courses for personal development.
  • Collaborates in a multidisciplinary environment with world leading clinicians, data scientists, biological experts, statisticians and IT professionals.

Education, Qualifications, Skills and Experience

Essential

  • M.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering) or have demonstrated an outstanding trackrecord of industry experience (2+ years) with the desired data science methodologies with a B.Sc. in a relevant field (such as mathematics, computer science, engineering).
  • Demonstrated experience with and a sound understanding of a variety of statistical and machine learning methods and standard statistical/ML development practices.
  • Practical software development skills in standard data science tools: Python, Code versioning (bitbucket/git), UNIX skills, familiarity working in cloud environment (AWS preferred)
  • Experience developing machine learning first products such as timeseries analysis, multiobjective optimization, forecasting, behavioral analysis
  • Strong communication and teamwork skills

Desirable

  • Ph.
D./M.Sc. degree in rigorous quantitative science (such as mathematics, computer science, engineering)

  • Interactive data visualization (interactive dashboards w/ DASH, plotly, etc.,)
  • Advanced experience with Kubernetes and machine learning product architecture
  • Advanced statistical and machine learning models such as hierarchical mixed bayesian models, transformerbased NLP models, reinforcement learning, deep learning models that span CNN/RNN/LSTM, GNNs, constrained optimization, stateoftheart timeseries & forecasting models
  • Experience in dataled solution delivery and software lifecycle development practices including Agile/Scrum, Waterfall, DevOps and/or CI/CD.
  • ML Ops experience: model tracking, model governance, multiple models in different production contexts
  • Communication, business analysis, and consultancy
  • Experience within the pharmaceutical industry
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