Job Description Summary

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use.
To manage the definition, implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or creation through enrichment, consumption, retention, and retirement, enabling the availability of useful, clean, and accurate data throughout its useful lifecycle. High agility to be able to work across various business domains. Integrate business presentations, smart visualization tools and contextual storytelling to translate findings back to business users with a clear impact.
Independently set strategy, manage budget, ensuring appropriate staffing and coordinating projects within the area supervised.
If managing a team: empowers the team and provides guidance and coaching, with limited guidance from more senior managers.   

Job Description

Major accountabilities: 

• Use data and advanced analytics to improve forecasts and support commercial decisions.
• Develop and maintain predictive models, statistical analyses, and machine learning
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• Analyze complex datasets and turn the findings into clear recommendations for business teams.
• Partner with cross-functional teams to understand business challenges and define analytical approaches that support strategic objectives.
• Develop and maintain dashboards, reports, and performance metrics to enable effective monitoring of key business outcomes.
• Ensure data quality, integrity, and consistency across analytical models, reporting processes, and data sources.
• Communicate analytical findings and insights clearly to technical and non-technical audiences
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• Contribute to the continuous improvement of forecasting methodologies, analytics capabilities, and data science best practices within the organization.

 Key performance indicators:

• Delivery of analytics projects on time and within scope.
• Forecast accuracy and predictive model performance.
• Stakeholder adoption of analytics and reporting outputs.
• Quality and accuracy of insights and recommendations.
• Business impact is generated through data-driven decision-making.
• Data quality and compliance with governance standards.

• Contribution to analytics innovation and capability building.

 Minimum Requirements: 
  Work Experience & Skills

• 7+ years of experience in data science, advanced analytics, business intelligence or  a related field.
  • Experience working with commercial or sales forecasting is highly desirable.
  • Experience in pharmaceutical, healthcare, and life sciences is an advantage.
  • Experience and ability to work with large datasets, preferably with Python or R.
  • Knowledge of machine learning techniques, predictive analytics, and statistical modeling.
  • Experience with data visualization tools such as Power BI, Python, or R visualization libraries.
  • Familiarity with cloud-based analytics platforms (Azure, AWS, or Google Cloud) is preferred.
  • Understanding of generative AI and advanced analytics applications is a plus.

 Languages :

• English.

Skills Desired

Apache Spark, Artificial Intelligence (AI), Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Machine Learning (Ml), Master Data Management, Python (Programming Language), R (Programming Language), Statistical Analysis