Data Scientist

Abbott Laboratories' Established Pharmaceuticals Division (EPD) is seeking a talented Data Scientist to join their Advanced Analytics team. This role is central to transforming the organization into a global, data-driven company, utilizing advanced technologies like Machine Learning, Deep Learning, Generative AI, and Computer Vision to achieve business objectives and drive growth.

As a Data Scientist, you will be instrumental in building and refining effective Data Science Solutions for Abbott EPD worldwide. You will rapidly move from identifying priorities and generating ideas to implementing solutions. Your responsibilities will include:

• Participating in and driving data collection, cleaning, analysis, and interpretation (EDA).
• Collaborating with business partners and product owners to conceptualize solutions for complex challenges.
• Generating insightful visualizations to effectively communicate findings.
• Performing model selection, validation, and contributing to deployment strategies in collaboration with the engineering team.
• Writing high-quality, deployable code.
• Sharing learnings and insights with fellow data scientists to foster a collaborative environment.
• Taking full responsibility for analysis and modeling tasks, collaborating closely with Senior Data Scientists.
• Building efficient Advanced Analytics solutions to meet business needs, maximizing the use of available market resources.
• Committing to continuous learning of the latest trends and technologies in data science.
• Working closely with Product Owners and the Engineering team to ensure timely, cost-effective, and high-quality delivery of the Data Science components of projects.
• Collaborating with and evaluating external vendors to ensure alignment with data science standards and project requirements.
• Engaging in hands-on data analysis, modeling, and prototyping of DS frameworks to produce high-quality outputs.

This is an individual contributor role, with no direct or indirect reports. You will be accountable for delivering targeted business impact per initiative in collaboration with key stakeholders and identifying future impactful opportunities. This role involves working with cross-functional teams to build innovative solutions for internal business functions across various geographies.

Minimum Education: Master or PhD in a relevant field such as applied mathematics, computer science, engineering, or applied statistics.

Minimum Experience:

• A minimum of 3-5 years of relevant working experience, preferably within the pharmaceutical industry.
• Solid experience in full-life cycle data science projects and applying data science methods to business problems (experience in financial/commercial or manufacturing/supply chain areas is a plus).
• Strong experience in data mining, statistical modeling, predictive modeling, and developing machine learning algorithms.
• Proven problem-solving ability in international settings, with a preference for experience in developing markets.
• Proven experience working in cloud environments, preferably AWS/Sagemaker.
• Practical experience in deploying machine learning solutions.
• Strong understanding of good software engineering principles and best practices.
• Ability to work with and guide cross-functional teams to bridge business and data science (consultancy experience is a plus).
• Intrinsic motivation to guide others 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 like Python or R, with proficiency in data manipulation, wrangling, and modeling techniques.
• Extensive experience building and debugging complex SQL queries.
• Excellent knowledge of statistical techniques, machine learning algorithms, and their practical implementation.
• Exceptional communication and presentation skills, capable of conveying complex concepts to both technical and non-technical audiences.
• A proven track record of delivering data-driven solutions with measurable business impact.
• 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.
• Fluency in English is mandatory; additional languages are a plus.