Head Data Science

Key Skills

Aartificial intelligence, Algorithms, Apache Hadoop, Apache Hive, Apache Kafka, AWS, Azure, Big Data Technology, C++, Data Analytics, Data science techniques, Java Programming, Leadership, Machine learning techniques, MATLAB Programming, NoSQL, Python Programming, R Programming, Snowflake, SQL

Job Description

• Leading Global Manufacturing Supply Data Science team.
• Owning, leading and driving functional Data Science strategy and objectives.
• Establishing, planning and administering overall functional data science policies and lifecycle management.
• Providing strategic prioritization and overall direction of functional data science efforts.
• Determining appropriate tools, techniques and methodologies that produces meaningful results.
• Overseeing and managing functional data strategy, data science needs and execution of initiatives.
• Facilitating value creation of functional data assets through advanced analytics approaches (including all AI disciplines) and transformation towards a real-time data-driven business unit.

How you will contribute:

• Global Manufacturing Supply (GMS) Data Science strategy implementation: Understanding and effectively working with a wide variety of manufacturing & supply chain data sources and archetypes.
• Provide thought leadership in concepts related to data acquisition and ingestion working with respective stakeholder groups. Understand respective systems security and provide support for data transparency, disclosure, and governance. Strategically connect with Takeda enterprise projects related Data Science.
• Detailed scale-up and delivery functional data science execution roadmap:
• Reviews data science possibilities/initiatives/requests in collaboration with stakeholders. Advises on the respective prioritization for short and medium focus.
• Data science capabilities:

  Ensures and reviews internal and external data science capabilities. Ensures data science capabilities are sufficient to defined data scientist profile. Conducts and participates in technical interviews for data science capabilities. Ensures and manages the data science training.

• Function’s Data Science portfolio
• Functional and cross-functional data science interdependencies
• Functional data science communities
• Quality, reliability, and access of data, creating value from internal and external data assets, developing advanced analytics capabilities, and supporting the development of Data Products that drive business and customer insights
• Actively manages and develops functional Data Science Team.
• Manages, drives and executes respective Data Science reporting in collaboration with stakeholder (e.g. automated daily/monthly/annual).
• Takes responsibility for functional OpEx and CapEx annual budgeting.

DIMENSIONS AND ASPECTS

Technical/Functional (Line) Expertise

• Strong expertise and experience in Digital/Big Data Analytics/ Artificial Intelligence/Machine Learning algorithms, respective programming knowledge
• Capabilities to translate business needs into data analytics concepts and the other way
• Hands-on, able to implement and execute data science initiatives, analysis, machine learning
• Agile project management skills

Leadership

• A firm grasp of industry, scientific and digital, artificial intelligence, machine learning and data science trends and market conditions, to develop solutions enhance compliance and quality of life for patients
• Role requires business partnership interface providing the Data Science link with cross-functional stakeholder
• Lead patient- and stakeholder centered best in class data science function, develop diverse data science talent and elevate organizational performance.

Decision-making and Autonomy

• DOA in line with TMAP
• Full accountability for decisions on the day to day functional Data Science operation
• Decisions are complex, covering all data science levels and technologies for GMS and therefore significantly impact Takeda’s ability to scale data science.

Interaction

• Role requires business partnership interface within and outside GMS to ensure alignment for data science priorities, roles, responsibilities and accountabilities.

Innovation

• Translate data science, artificial intelligence and machine learning trends and technology into execution.

Complexity

• Impact across the full portfolio of strategic products.
• Ability to interface with international stakeholders and to connect internal and.

  external data analytics experts of both academia and industries – high change management complexity.

• Capabilities to translate business needs into data analytics concepts and the other way.
• Still Hands-on, able to implement and execute initiatives.

What you bring to Takeda:

Education / Experience:

• Minimum 5+years of people management & leadership experience.
• Advanced degree required e.g. in Data Science, Computer Science, Engineering, Mathematics, Statistics, Physics, Economics or similar.
• Pharmaceutical or other industry experience in applying and executing Digital/Big Data Analytics/ Artificial Intelligence/Machine Learning, Machine Learning algorithms, Respective programming knowledge.
• Excellent presentation and communication skills with ability to tell a story in a clear and concise manner to technical and non-technical audiences.
• Skilled in agile product development.
• Fluent in English.

Digital & Data Science Skills:

• Strong expertise and experience in Digital/Big Data Analytics/ Artificial Intelligence/Machine
• Experience in Machine Learning algorithms .
• Knowledge of MATLAB/Python/R required.
• Further skills, e.g., of AWS, Azure, C++,SQL, NoSQL, Hadoop, Snowflake, Kafka, Hive etc. are advantageous.

.Behaviors:

• Strategic enterprise thinking, finding innovative ways to serve patients build reputation and trust.
• Creating a diverse, equate and inclusive environment that inspires and enables people.
• Focusing on the few priorities and provide superior results.
• Elevating capabilities for now and the future.