Post Market Surveillance Data Science Expert

Key Skills

Aartificial intelligence, AWS Sagemaker, Data science techniques, Deep Learning, Machine learning techniques, NumPy, Pandas, PySpark, Python Programming, PyTorch, R Programming, Scikit-learn, SQL, TensorFlow

Job Description

We are seeking an experienced and highly skilled Senior Data Science Expert with a proven track record of at least 10+ years in the field. The ideal candidate will be responsible for leading and executing complex data science projects, leveraging advanced statistical and machine learning techniques to derive actionable insights and solutions. The Senior Data Science Expert will play a pivotal role in shaping the data science strategy of the department and mentoring junior team members.

Serves as a liaison between Medical Affairs, Clinical Affairs, Research & Development, and Complaint Handling to ensure Post Market Surveillance and Risk Management processes are executed end-to-end .

Reviews and prepares reports on aggregate data and provides recommendation for further escalation. Reviews complaint trend analysis, product risk assessments including Health Hazard Evaluations, clinical evaluation reports, risk management reports and FMEAs. Assists in benchmarking best practices with world-class organizations, interfaces with notified body, and/or other regulators, and provides input to establish metrics.

Hands on Technical lead:

• Create analytical solutions for PMS business by combining various data science tools, applied statistics, AI/ML and NLP techniques

• Identify key data sources and automate data collection processes .

• Undertake preprocessing of structured and unstructured data by partnering with data engineers.

• Perform data exploration and feature engineering for the model development .

• Support in NLP Research, building reproducible codes, creating & maintaining bag of words

• Have good understanding of MLops

• As part of PMS CoE perform extensive research and maintain a backlog for potential data science application using prebuilt models.

• Build predictive models and machine-learning algorithms to detect signal , complaint trends and trends over time .

• Combine models through ensemble modeling.

• Present information using data visualization techniques in the appropriate business context .

• Partner with other technology teams /external analytical solution providers and drive execution of data science initiatives /programs.

• Support PMS (Post Market Surveillance) COE data science operations for the Signal detection models.

Model Development and Implementation:

• Utilize advanced statistical and machine learning techniques to develop predictive models and algorithms for Post Market Surveillance use cases.

• Oversee the implementation& Deployments of models into production systems, ensuring scalability and performance.

Data Exploration and Feature Engineering:

• Lead data exploration efforts to identify relevant patterns and trends.

• Collaborate with data engineers to ensure the availability of high-quality data for analysis.

Mentorship and Collaboration:

• Mentor and guide junior data scientists, fostering a culture of continuous learning and development.

• Collaborate with engineering and other CoE teams to foster innovation .

• Collaborate with other departments to integrate data science solutions into business processes.

Communication and Visualization:

• Be an enabler for adhering to product quality , patient safety and meet standards of FDA , EU-MDR and other governing bodies across regions , zones and country .

• Communicate complex technical concepts to non-technical stakeholders in a clear and understandable manner.

• Create visualizations and reports to effectively communicate insights derived from data.

Continuous Learning:

• Stay abreast of the latest advancements in data science, machine learning, and related technologies.

• Propose and implement innovative approaches to enhance the organization's data science capabilities.

Project Management:

• Lead discussions and assess the feasibility of AI/ML solutions for business problems ( Process & Modernization ).

• Lead end-to-end data science projects from problem definition, data exploration, model development, to deployment.

• Ensure projects are delivered on time, within scope, and meet high-quality standards.

Qualifications:

• Minimum of 10+ years of experience in data science, machine learning, and statistical modeling.

• Advanced degree (Ph.D. or Master’s or equivalent) in a relevant field such as Computer Science, Statistics, or Mathematics.

• Proven expertise in programming languages such as Python or R.

• Strong knowledge of data manipulation and analysis tools (e.g., Pyspark,Pandas, NumPy, SQL).

• Experience with machine learning Platforms/frameworks /packages/libraries (e.g., Databricks ML ,Pivotal Foundry , AWS Sagemaker (Hugging Face )Sci-kitlearn, TensorFlow, PyTorch) and model deployment.

• Strong analytical skills with proficiency in application of statistical analysis and machine learning algorithms like text analytics, topic modelling, Deep learning, transformers,ensamble models

• Demonstrated leadership and project management skills.

• Enthuse to collaborate with various stakeholders across the organization and take complete ownership of deliverables.

 The Senior Data Science Expert will play a key role in advancing our organization's data-driven decision-making capabilities and contribute significantly to the success of our data science initiatives.

About Philips

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If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.