Sr. Manager, Data Scientist - Biopharma

Key Skills

AngularJS, Apache Hadoop, Dash framework, Data Analytics, Data Mining, Data science techniques, Database, Databricks, Effective communication skills, Machine learning techniques, Python Programming, Snowflake, SQL, Tableau

Job Description

ROLE SUMMARY:

The Commercial Analytics team at Pfizer is looking for a full-stack Senior Data Scientist Manager who is passionate about crafting and implementing predictive modeling and statistical analysis to build end-to-end solutions and insights that have a direct impact on patient's lives and the future of Pfizer as a data-driven organization. You will be a thought partner to the business, understand strategic goals, and then use your skills and subject matter expertise to surface impactful insights that drive business decisions and patient benefits. With colleagues across the globe, our rigorous analytical expertise is relied upon as the compass and decision support for the enterprise. Our dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including market research, data science, digital analytics, finance, and consulting. Our culture is about getting things done iteratively and rapidly, with open feedback and debate along the way. We believe Data Science is a team sport, but we strive for independent decision-making and taking smart risks.

ROLE RESPONSIBILITIES:

This role is accountable for delivering data science driven support for an assigned brand and will partner with US Commercial, business, and digital teams, to develop and implement models, insights, and data products that drive brands’ strategic priorities.

• Take deep dives in large-scale data to identify key insights that will shape future product/brand strategy for a specific therapeutic area
• Collaborate with cross-functional teams to identify new growth opportunities, develop data requirements, establish critical metrics, and evangelize data products
• Design, deploy, and evaluate experiments that help define opportunities for higher adoption, improved business performance, and better patient experience
• Conduct hypothesis-driven exploratory analyses, select appropriate ML algorithms, and build complex optimization engines to deliver impactful data solutions!
• Research new technologies and methods across data science and data engineering to improve the technical capabilities of the team
• Communicate insights to senior management by distilling complex analysis and concepts into concise business-focused takeaways

QUALIFICATIONS:

• Bachelor’s degree with 7+ years of experience OR Masters Degree with 6+ years of experience OR PhD with 2+ years of experience
• Degree preferably in engineering, economics, statistics, computer science, or related quantitative field.
• Preferred experience in Applied Econometrics, Statistics, Data Mining, Machine Learning, Analytics, Mathematics, Operations Research, Industrial Engineering, or related field preferred.
• Working knowledge of relational databases, including SQL, and large-scale distributed systems such as Hadoop and or working in Snowflake/Databricks
• Ability to implement data science pipelines and applications in a general programming language such as Python, Scala, Java, or R.
• Practical experience with and theoretical understanding of ML algorithms for classification, regression, clustering, and anomaly detection
• Well versed with and have experience applying various statistical methodologies including Bayesian and non-parametric techniques, hypothesis testing, ANOVA, Regression, fixed and random effects etc. to measure the impact of experiments
• Hands on experience working in big data environments such as Hadoop, Spark, and using Python / SQL or comparable languages for manipulating and analyzing complex clickstream and or unstructured data
• Ability to extract significant business insights from data and identify the roots behind the patterns
• Experience working with a data visualization tool/package, including Dash, Tableau, and Angular etc.
• Communication skills for communicating complex quantitative analyses to senior business executives
• Candidate demonstrates a breadth of diverse leadership experiences and capabilities including: the ability to influence and collaborate with peers, develop and coach others, oversee and guide the work of other colleagues to achieve meaningful outcomes and create business impact.