Senior Data Scientist(Data & Analytics) - Python
Amgen
Senior Data Scientist(Data & Analytics) - Python
Job Description
Career CategoryProcess DevelopmentJob DescriptionHow might you defy imagination? At Amgen, our shared mission to serve patients drives all that we do. In this vital role, you will join Amgen's Transformative Digital Capabilities (TDC) organization within Process Development and help accelerate digital transformation through analytics, data products, and AI-enabled solutions. What will you do As a Data Scientist, you will partner with scientists, engineers, business stakeholders, and technology teams to unlock the value of Process Development data. You will lead analytical initiatives that improve decision-making, increase data accessibility and usability, and enable scalable digital and AI capabilities across Process Development. You will work across a range of initiatives spanning data strategy, advanced analytics, process optimization, digital products, and data science solutions that improve business outcomes and accelerate innovation. A successful candidate will independently manage multiple assignments, anticipate and prevent potential problems, develop practical solutions aligned to operational objectives, and provide guidance to other professionals. Job Requirements Partner with stakeholders to identify and prioritize opportunities where analytics, AI, or data science can drive measurable value. Lead the design and development of analytical solutions, dashboards, models, and data products that support scientific and business decision-making. Apply statistical, machine learning, and data science methods to solve complex business and scientific problems. Drive exploratory analysis, trend analysis, forecasting, and modeling using multiple sources of data. Contribute to the development and deployment of AI-enabled solutions, including machine learning and generative AI use cases where appropriate. Improve data accessibility, usability, quality, and stewardship in partnership with data, product, and engineering teams. Translate business problems into analytical approaches, define success metrics, and communicate recommendations to technical and non-technical audiences. Lead or co-lead small projects or workstreams and provide guidance to peers on analytical methods and best practices. Help shape standards and repeatable approaches for analytics, visualization, and data science delivery. Stay current with emerging technologies, data science methodologies, and industry best practices and apply them pragmatically to Amgen's environment. Basic Qualifications Master's degree OR Bachelor's degree and 7 - 11 years of relevant experience Preferred Qualifications Experience applying data science, analytics, or statistical methods to solve complex business or scientific problems. Strong proficiency in Python, R, SQL, or related analytical programming and query languages. Experience designing dashboards and visualizations using Spotfire, Tableau, Power BI, or similar tools. Experience developing and deploying analytical models, decision-support tools, or data products. Understanding of data governance, metadata, data quality, and data management principles. Familiarity with machine learning, AI, and generative AI concepts and practical applications. Strong stakeholder engagement and communication skills with the ability to explain analytical insights clearly. Experience working in cross-functional teams and Agile environments. Experience in biotechnology, pharmaceuticals, manufacturing, or other regulated industries preferred. .
Locations
- India - Hyderabad
Skills Required
- Pythonintermediate
- machine learningintermediate
- biotechnologyintermediate
Required Qualifications
- Partner with stakeholders to identify and prioritize opportunities where analytics, AI, or data science can drive measurable value. (experience)
- Partner with stakeholders to identify and prioritize opportunities where analytics, AI, or data science can drive measurable value. (experience)
- Lead the design and development of analytical solutions, dashboards, models, and data products that support scientific and business decision-making. (experience)
- Lead the design and development of analytical solutions, dashboards, models, and data products that support scientific and business decision-making. (experience)
- Apply statistical, machine learning, and data science methods to solve complex business and scientific problems. (experience)
- Apply statistical, machine learning, and data science methods to solve complex business and scientific problems. (experience)
- Drive exploratory analysis, trend analysis, forecasting, and modeling using multiple sources of data. (experience)
- Drive exploratory analysis, trend analysis, forecasting, and modeling using multiple sources of data. (experience)
- Contribute to the development and deployment of AI-enabled solutions, including machine learning and generative AI use cases where appropriate. (experience)
- Contribute to the development and deployment of AI-enabled solutions, including machine learning and generative AI use cases where appropriate. (experience)
- Improve data accessibility, usability, quality, and stewardship in partnership with data, product, and engineering teams. (experience)
- Improve data accessibility, usability, quality, and stewardship in partnership with data, product, and engineering teams. (experience)
- Translate business problems into analytical approaches, define success metrics, and communicate recommendations to technical and non-technical audiences. (experience)
- Translate business problems into analytical approaches, define success metrics, and communicate recommendations to technical and non-technical audiences. (experience)
- Lead or co-lead small projects or workstreams and provide guidance to peers on analytical methods and best practices. (experience)
- Lead or co-lead small projects or workstreams and provide guidance to peers on analytical methods and best practices. (experience)
- Help shape standards and repeatable approaches for analytics, visualization, and data science delivery. (experience)
- Help shape standards and repeatable approaches for analytics, visualization, and data science delivery. (experience)
- Stay current with emerging technologies, data science methodologies, and industry best practices and apply them pragmatically to Amgen's environment. (experience)
- Stay current with emerging technologies, data science methodologies, and industry best practices and apply them pragmatically to Amgen's environment. (experience)
- Master's degree OR Bachelor's degree and 7 - 11 years of relevant experience (experience, 11 years)
- Master's degree OR Bachelor's degree and 7 - 11 years of relevant experience (experience, 11 years)
Preferred Qualifications
- Experience applying data science, analytics, or statistical methods to solve complex business or scientific problems. (experience)
- Experience applying data science, analytics, or statistical methods to solve complex business or scientific problems. (experience)
- Strong proficiency in Python, R, SQL, or related analytical programming and query languages. (experience)
- Strong proficiency in Python, R, SQL, or related analytical programming and query languages. (experience)
- Experience designing dashboards and visualizations using Spotfire, Tableau, Power BI, or similar tools. (experience)
- Experience designing dashboards and visualizations using Spotfire, Tableau, Power BI, or similar tools. (experience)
- Experience developing and deploying analytical models, decision-support tools, or data products. (experience)
- Experience developing and deploying analytical models, decision-support tools, or data products. (experience)
- Understanding of data governance, metadata, data quality, and data management principles. (experience)
- Understanding of data governance, metadata, data quality, and data management principles. (experience)
- Familiarity with machine learning, AI, and generative AI concepts and practical applications. (experience)
- Familiarity with machine learning, AI, and generative AI concepts and practical applications. (experience)
- Strong stakeholder engagement and communication skills with the ability to explain analytical insights clearly. (experience)
- Strong stakeholder engagement and communication skills with the ability to explain analytical insights clearly. (experience)
- Experience working in cross-functional teams and Agile environments. (experience)
- Experience working in cross-functional teams and Agile environments. (experience)
- Experience in biotechnology, pharmaceuticals, manufacturing, or other regulated industries preferred. (experience)
- Experience in biotechnology, pharmaceuticals, manufacturing, or other regulated industries preferred. (experience)
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