Senior Global Machine Learning Engineer

4 semanas atrás

Coimbra, Coimbra, Portugal Olympus Europa Se & Co. Kg Tempo inteiro
Job Title: Senior Global Machine Learning Engineer

Olympus Europa Se & Co. Kg is seeking a seasoned Senior Global Machine Learning Engineer to join our team. As a key member of our Global Insights & Analytics team, you will play a crucial role in driving the transformation towards becoming a global, data-driven MedTech company.

Responsibilities:
  • Takes ownership and drives the adoption of best practices, standards, and methodologies to maintain high-quality data science work within their assigned Advanced Analytics capability area.
  • Conveys the message and value of their area of capabilities (e.g., AI) to the organization, influencing decision-making processes and becoming a trusted advisor for the key business stakeholders and relevant communities.
  • Stays up-to-date with the latest advancements and innovations in their domain, actively bringing in new knowledge to enhance the team's capabilities.
  • Evaluates and recommends new technologies, tools, and Data Science / Machine Learning techniques to enhance data science processes and improve efficiency.
  • Fosters a culture of continuous learning and growth within the team, encouraging professional development and knowledge sharing.
  • Collaborates with stakeholders across the organization to understand their business objectives and define data-driven solutions that align with these objectives.
  • Works closely with the Analytics Product Owners and the Cloud/Engineering team to ensure delivery of the Data Science / Machine Learning part of the projects within time, cost, and quality.
  • Collaborates with external vendors, evaluating their capabilities and ensuring their alignment with data science / machine learning standards and project requirements.
  • Continuously engages in hands-on data analysis, modeling, and prototyping DS frameworks to deliver high-quality outputs.
  • Collaborates with cross-functional teams to define data-driven solutions that align with the organization's objectives and optimize decision-making processes.
  • Produces high-quality code that allows the team to build scalable solutions and put solutions into production.
  • Leads and oversees several ideation and scoping sessions with business stakeholders to determine the data needed to answer specific questions or problems related to the business.
  • Takes a lead role, and oversees, mentors, and coaches others in the development, deployment, and integration of prioritized Advanced Analytics solutions in collaboration with local/regional cross-functional teams and/or external partners.
  • Takes ownership of identifying, defining, and completing required documentation, demos or presentations as needed.
  • Oversees, conceptualizes, drives, and continuously refines Advanced Analytics guidelines and standards by synthesizing learnings from prioritized Advanced Analytics initiatives.
Requirements:
  • Master or PhD in relevant field (e.g., applied mathematics, computer science, engineering, applied statistics).
  • At least 4-6 years of relevant working experience, ideally in pharma/healthcare/MedTech.
  • Solid experience working on full-life cycle data science; experience in applying data science methods to business problems (experience in the financial/commercial or manufacturing/supply chain areas a plus).
  • Strong experience in data mining, statistical modeling, predictive modeling, and development of machine learning algorithms.
  • Proven problem-solving ability in international settings, preferably with developing markets.
  • Proven experience in working in a cloud environment, preferably Azure.
  • Practical experience in deploying machine learning solutions.
  • Strong understanding of good software engineering principles and best practices.
  • Ability to work and lead cross-functional teams to bring business and data science closer together - consultancy experience a plus.
  • Intrinsic motivation to guide people and make Advanced Analytics more accessible to a broader range of stakeholders.
  • Deep domain expertise in a specific field, such as Artificial Intelligence, Machine Learning, Natural Language Processing, or Computer Vision.
  • Strong programming skills in languages such as Python or R, with proficiency in data manipulation, wrangling, and modeling techniques.
  • Strong experience building and debugging complex SQL queries.
  • Excellent knowledge of statistical techniques, machine learning algorithms, and their practical implementation in real-world scenarios.
  • Exceptional communication and presentation skills, with the ability to convey complex concepts and insights to both technical and non-technical stakeholders.
  • Proven track record of delivering data-driven solutions that have had a measurable impact on business outcomes.
  • Exposure to big data technologies (e.g., Hadoop, Spark) is highly desirable.
  • Demonstrated ability to drive the adoption of data science best practices, standards, and methodologies within an organization.
  • Fluency in English a must, additional languages a plus.

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