Senior Data Scientist
TraceLink’s software solutions and Opus Platform help the pharmaceutical industry digitize their supply chain and enable greater compliance, visibility, and decision making. It reduces disruption to the supply of medicines to patients who need them, anywhere in the world.
Founded in 2009 with the simple mission of protecting patients, today Tracelink has 8 offices, over 800 employees and more than 1300 customers in over 60 countries around the world. Our expanding product suite continues to protect patients and now also enhances multi-enterprise collaboration through innovative new applications such as MINT.
Tracelink is recognized as an industry leader by Gartner and IDC, and for having a great company culture by Comparably.
The rapidly changing landscape of pharmaceutical supply chains calls for robust, dynamic data solutions. TraceLink, at the forefront of this change, harnesses the potential of big data and cloud technologies using sophisticated algorithms, data science, and analytics. We're expanding our core team and are on the lookout for an experienced Senior Data Scientist. This role demands a deep understanding of data analytics combined with a strategic mindset to drive innovation, recognize trends, and influence key business decisions.
Drive the conceptualization, development, and deployment of advanced data analytics solutions and predictive models.
Collaborate with cross-functional teams to translate complex business requirements into actionable data-driven solutions.
Explore and introduce the latest data science techniques and technologies to keep TraceLink at the cutting edge.
Advocate for data-driven decision-making across departments, presenting insights and recommendations to executive leadership.
Ensure the integrity, reliability, and timeliness of data sources and analytical outputs.
Stay updated with industry trends, challenges, and opportunities to refine and improve our analytical approaches continuously.
Skills and Experience
Master’s or Ph.D. in Data Science, Mathematics, Computer Science, Engineering, or a related field.
Proven experience in leading data science projects from conception to realization.
Proficiency in data analytics tools and languages such as Python, R, SQL, and Java.
Experience with big data technologies, particularly within cloud environments like Amazon Web Services.
Strong knowledge of applied mathematics including but not limited to probability, statistics, optimization, and machine learning.
Ability to communicate complex data findings in a clear and impactful manner to a non-technical audience.
Familiarity with agile methodologies and an iterative approach to problem-solving.
Dedication to continuous improvement and professional development.