Data Scientist at Drugstoc eHub Limited

About the job

• The Data Scientist will provide advanced analytical insights, predictive models, and data-driven recommendations to support strategic business decisions across DrugStoc. This role is responsible for generating actionable leads, uncovering growth opportunities, optimizing operational performance, and empowering the Business Intelligence team, including Data Analysts with deep analytical insights and scalable data solutions.
• The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

Key Responsibilities

• Develop predictive models, clustering systems, and machine-learning algorithms to identify business opportunities and customer behavior patterns.
• Provide actionable insights and lead-generation intelligence to the BI team, Sales, Operations, and Leadership.
• Analyze large and complex datasets to identify trends, risks, inefficiencies, and revenue-expansion opportunities.
• Collaborate closely with Data Analysts to enhance dashboards, reports, and data pipelines.
• Build data products and automated scoring models to improve decision-making.
• Conduct exploratory data analysis (EDA) and design experiments for hypothesis testing.
• Translate business challenges into data-science solutions and provide clear recommendations to stakeholders.
• Ensure data quality, integrity, and alignment with DrugStoc’s data governance standards.
• Prepare periodic analytical reports highlighting key insights, forecasts, and operational risks.

Qualifications

• Bachelor’s degree in data science, Statistics, Computer Science, Mathematics, Engineering, or a related field.
• 3–5+ years experience in data science, machine learning, or advanced analytics (health-tech or supply chain experience is an added advantage).
• Strong proficiency in Python or R (pandas, scikit-learn, NumPy, TensorFlow/PyTorch).
• Strong SQL skills and experience working with large datasets.
• Experience building predictive models, statistical analysis, and data visualization.
• Familiarity with BI tools (Power BI, Tableau, Looker) and collaborative work with Data Analysts.
• Excellent analytical thinking, problem-solving, and communication skills.
• Ability to translate complex data findings into simple, actionable insights for business teams.