Data Scientist I Full-time NEW

Data Scientist I – Commercialization & EF DS & AI Solutions

The Data Scientist I position is a foundational role within the analytics team, requiring strong analytical rigor, strong machine learning fundamentals, and the ability to translate data into meaningful business solutions.

The Data Scientist I contributes to predictive, analytical, and AI-driven solutions across multiple business domains (e.g., forecasting, commercial analytics, decision support). Working under the guidance of senior data scientists, this role emphasizes hands-on modelling, analytical problem-solving, and engineering discipline, while building the depth to own more complex workstreams over time.

Roles & Responsibilities:

• Assist in the analysis and interpretation of structured and unstructured data to support business decisions and operational improvements.
• Contribute to the development of predictive and analytical models using statistical, machine learning, and optimization techniques.
• Assist in feature engineering, model training, evaluation, and performance diagnostics under guidance from senior team members.
• Collaborate with team members and stakeholders to understand business requirements and contribute to the design, development, and maintenance of basic data pipelines, models, and dashboards.
• Support the development and enhancement of data infrastructure and analytical tools/product development under guidance from senior data scientists and LT teams.
• Prepare and present clear, concise reports and visualizations to communicate findings to technical and non-technical audiences.
• Follow technical best practices in coding, documentation, and version control to ensure reproducibility and scalability of analytics solutions.
• Continuously build expertise in data science, machine learning, and applied analytics techniques.
• Stay curious about emerging AI/ML methods and their business applications.

Skills and Competencies:

• Strong foundations in statistics, probability, and machine learning concepts.
• Familiarity with data analytics and machine learning libraries (e.g., pandas, NumPy, Scikit-learn, TensorFlow).
• Ability to perform structured problem decomposition and analytical reasoning.
• Exposure to predictive modeling techniques (e.g., regression, classification, basic time-series concepts).
• Familiarity with model evaluation metrics and validation approaches.
• Ability to communicate technical concepts clearly and effectively to team members and stakeholders.
• Willingness to learn new technologies and adapt to evolving project requirements.
• Strong problem-solving skills and attention to detail.

Experience:

• Bachelor's or master's degree in Computer Science, Information Technology, Engineering, or a related analytical discipline.
• Internship, academic, or early-career experience in data science, analytics, machine learning, or software engineering.
• Exposure to real-world data challenges through academic projects, internships, or hackathons.
• Hands-on experience in data preprocessing, feature engineering, and model development.

Good to Have:

• Exposure to time-series or forecasting techniques (e.g., trend/seasonality modeling, ARIMA, Prophet).
• Familiarity with MLOps concepts such as model tracking, reproducibility, and deployment basics.
• Exposure to cloud-based data solutions and modern analytics stacks.
• Awareness of GenAI or LLM-based tools and their potential role in analytical workflows.
• Strong interest in continuous learning and building deep technical expertise in data science

If you come across a role that intrigues you but doesn't perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.

Uniquely Interesting Work, Life-changing Careers With a single vision as inspiring as “Transforming patients' lives through science™ “, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.