Vaga de Senior Global ML engineer / Data Scientist
1 vaga: | Publicada em 11/05
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Sobre a vaga
Senior Global ML engineer / Data Scientist
Olympus Medical Products Portugal (OMPP) | Corporate
Type of employment:
Permanent employment
Function:
IT
Location:
Full Remote (allocated to Coimbra office)
Olympus Medical Products Portugal is a subsidiary of the Olympus Group. At
Olympus, we are committed to Our Purpose of making peoples lives healthier, safer
and more fulfilling. As a global medical technology company, we partner with
healthcare professionals to provide best-in-class solutions and services for early
detection, diagnosis and minimally invasive treatment, aiming to improve patient
outcomes by elevating the standard of care in targeted disease states.
The Global Insights & Analytics team at Olympus Corporation helps define and lead
the transformation towards becoming a global, data-driven MedTech company with the
help of data and modern data technologies (e.g., Machine Learning, Deep Learning).
To us, Data and Advanced Analytics is an important lever to reach our business
targets, now and in the future; It helps differentiate ourselves from our
competition and ensure sustainable revenue growth at optimal margins. Olympus is
now looking for seasoned Senior ML engineers / Data scientists to help scope,
build and refine effective Data Science Solutions for Olympus world-wide. The
Senior ML engineer / Data scientist would work with a team of seasoned Data
solutions and Cloud Architects, DataOps/MLOps engineers and Data Engineers to help
drive the transformation towards effective data usage within Olympus, in tight
collaboration with business stakeholders and Analytics Product owners. Your
responsibilities
A Senior ML engineer / Data Scientist rapidly navigates from identifying priorities and helping to generate ideas to implementing solutions. He/she:
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 becomes 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 recommend 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.
Collaborate 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.
Collaborate with external vendors, evaluating their capabilities and ensuring
their alignment with data science / machine learning standards and project
requirements.
Continuously engage in hands-on data analysis, modeling, and prototyping DS
frameworks to deliver high-quality outputs.
Collaborate with cross-functional teams to define data-driven solutions that align
with the organization's objectives and optimize decision-making processes.
Produce high-quality code that allows the team to build scalable solutions and put
solutions into production
Lead and oversee several ideation and scoping sessions with business stakeholders
to determine the data needed to answer specific questions or problems related to
the business.
Take a lead role, and oversee, mentor, and coach others in the development,
deployment, and integration of prioritized Advanced Analytics solutions in
collaboration with local/regional cross-functional teams and/or external partners.
Take ownership of identifying, defining, and completing required documentation,
demos or presentations as needed.
Oversee, conceptualize, drive and continuously refine Advanced Analytics
guidelines and standards by synthesizing learnings from prioritized Advanced
Analytics initiatives.
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 e.g., data mining, statistical modelling, predictive
modelling, and development of machine learning algorithms
Proven problem-solving ability in international settings preferably with
developing markets
Proven experience in working in cloud environment preferably Azure
Strong experience working on full-life cycle data science; experience in applying
data science methods to business problems
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.
Global position
Work in a multicultural and diverse environment
Referral commission
Medical Health Insurance
Initial and continuous training
24 vacation days off
Day off on your birthday
Christmas Eve off
About Olympus Corporate
The Corporate Division is responsible for centralized functions that include
Finance and Controlling, HR, IT, Quality Management and Supply Chain Management.
It provides essential services and support to all business divisions. Moreover, it
is an important project initiator and leader within the international network.
About Olympus Corporate
The Corporate Division is responsible for centralized functions that include
Finance and Controlling, HR, IT, Quality Management and Supply Chain Management.
It provides essential services and support to all business divisions. Moreover, it
is an important project initiator and leader within the international network.