обновлено 8 дней назад
Manager, Data Engineering (AI)
168 800 - 253 250$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Manager, Data Engineering (AI): Leading data science and analytics initiatives for a medical device company developing Omnipod diabetes technologies with an accent on machine learning, cloud analytics pipelines, and healthcare data. Focus on managing data scientists, building automated reporting and predictive models, and translating complex datasets into business and patient insights.
Location: San Diego, California, United States
Annual base salary: $168,800–$253,250, with potential incentive compensation.
Company
is a medical device company developing the Omnipod tubeless insulin delivery platform and related technologies for diabetes care and other therapeutic areas.
What you will do
- Lead a team of data scientists and mentor team members while supporting retention and professional development.
- Partner with IT, executives, and cross-functional leaders to identify and deliver high-value data science opportunities.
- Own the analytics data products and insights delivery portfolio.
- Guide the development and deployment of automated machine learning and analytics pipelines using cloud technologies such as Azure, AWS, and GCP.
- Perform data cleaning, aggregation, statistical analysis, predictive modeling, and automated reporting across business, product, and patient data.
- Manage the annual budget and communicate findings, objectives, and procedures to stakeholders.
Requirements
- Master’s degree with 5+ years of experience, or PhD with 3+ years of experience, in data science, mathematics, computer science, electrical and computer engineering, or a related field.
- At least 2 years of experience with machine learning, artificial intelligence, or statistical inference.
- Direct team management experience in a fast-paced environment, preferably in medical device or healthcare industries.
- Experience with Python or R, SQL, relational databases, cloud computing, and big data technologies such as Databricks and Spark on Azure or AWS.
- Knowledge of software engineering principles, analytics processes, business intelligence tools, and effective stakeholder communication.
- Knowledge of diabetes pathophysiology, insulin signaling, or human physiology.
Nice to have
- Knowledge of non-relational databases such as MongoDB.
- Experience with business intelligence tools such as Spotfire, Tableau, or Cognos.
Culture & Benefits
- Fast-growing environment with career growth opportunities.
- Medical, dental, and vision insurance.
- 401(k) with company match.
- Paid time off and employee wellness programs.
- Occasional travel of less than 10% may be required.
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