Lead - Data Scientist - Pharma (5-7 yrs)

Job Description:

- We are seeking a dynamic and experienced Lead to join our team who will play a pivotal role in understanding client requirements, assessing existing ecosystems, and leading the implementation for our pharma client.

- Work closely with team to comprehend client requirements and varied objectives including (but not limited to) implementation of Omnichannel strategy.

- Lead the assessment of existing ecosystems across key pillars, including client portfolio plans & objectives, technical architecture, data models etc Collaborate with cross-functional teams to design and implement the optimal solution, ensuring seamless integration with existing processes.

- Leverage pharma industry exposure to provide strategic insights and recommendations for stated client objectives.

- Demonstrate proficiency in understanding and working with diverse pharma datasets, and assess their suitability for integration into the proposed solution.

- Apply data science skills, with expertise in MLOps being a significant plus, to ensure robust and scalable model deployment.

- Foster strong client relationships, serving as a trusted advisor and ensuring client satisfaction throughout the implementation process.

- Provide training and support to internal teams to ensure smooth and continued success on project implementations.

- Handle multiple projects at any point in time, ensuring that progress is made across all the projects, with appropriate prioritization and workload distribution within the team.

- Develop and disseminate innovative analytical techniques, processes and tools, that can be leveraged across projects / engagements.

- Monitor industry trends and implement best practices to improve in-house capabilities.

Desired Profile:

- Bachelor's or Master's degree in Computer Science, Data Science, Pharmaceutical Sciences.

- 5+ overall years of experience in leading analytical projects in pharma domain.

- 5+ years of experience advanced analytics including AI, machine learning, predictive modelling, advanced analytics and statistics modelling Experience in pharma commercial analytics is a plus.

- Proven track record of successfully implementing omnichannel strategy or similar technologies in the pharmaceutical or related industry.

- Strong understanding of the pharma ecosystem and familiarity with key data sources (Digital, sales, CRM, APLD), industry trends, and compliance requirements.

- Excellent understanding of machine learning techniques and algorithms, such as XGBoost, Random Forest, Linear, Logistic Regression, k-NN, Naive Bayes, SVM, Decision Trees, Neural Nets, Transfer Learning, NLP etc.

- Experience in areas of risk-score modelling, customer segmentation, impact assessment, attribution analytics, collaborative filtering, marketing mix modelling, recommendation engines and natural language processing is highly preferred.

- Proficiency in data science techniques and tools including Python, SQL, PySpark, Dataiku, AWS cloud services, Git, Tableau, PowerBI, etc.

- Experience in MLOps being a significant advantage

- Exceptional client management and communication skills, with a demonstrated ability to build and nurture relationships.

- Strong analytical and problem-solving abilities, with a keen attention to detail.

- Excellent project management skills, including the ability to prioritize tasks, manage timelines, and deliver on.