Principal Data Scientist, Global DD&T(Data, Digital & Technology), Japan

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Job Description

Please note this job requires business level Japanese in speaking, writing, and reading.

タケダの紹介

タケダは「世界中の人々の健康と輝かしい未来に貢献する」ことを企業の存在意義（パーパス）としています。そして目指す未来を共有しながら、一人ひとりが自分の可能性を引き出し、お互いの個性を認め合う、多様性にあふれた先進的な組織作りに取り組んでいます。私たちと一緒に、世界中の人々のいのちに貢献し、さらなる成長と活躍を目指しませんか。

タケダはグローバルな研究開発型のバイオ医薬品のリーディングカンパニーです。従業員は創業時から受け継いできたタケダの価値観であるタケダイズム（誠実＝公正・正直・不屈）を道しるべとしながら、患者さんに寄り添い（Patient）人々と信頼関係を築き（Trust）社会的評価を向上させ（Reputation）持続可能な事業を発展させる（Business）を日々の行動指針としています。

”Better Health for People, Brighter Future for the World” is the purpose of a company. We aim to create a diverse and inclusive organization where people can thrive, grow and realize their own potential while enabling our purpose. We continue to innovate and drive changes that will transform the lives of patients. We’re looking for like-minded professionals to join us.

Takeda is a global values-based, R&D-driven biopharmaceutical leader. We are guided by our values of Takeda-ism, which has been passed down since the company’s founding. Takeda-ism incorporates Integrity, Fairness, Honesty, and Perseverance, with Integrity at the core. They are brought to life through actions based on Patient-Trust-Reputation-Business, in this order.

OBJECTIVES/PURPOSE:

• Lead the design, development, and deployment of advanced data science and Artificial Intelligence (AI) solutions to address complex business challenges

• Collaborate with cross-functional teams to integrate data-driven insights into business strategies and operations

• Develop best practices and frameworks for AI and data science methodologies and tools

• Drive code quality and consistency processes ensuring high-quality, efficient, and secure AI and data science, while also fostering a culture of continuous improvement and collaboration

• Drive and accelerate Takeda’s community of data scientists culture, accelerating continuous learning and improvement

ACCOUNTABILITIES:

• Define and implement AI & data science solutions supporting Takeda’s global strategic AI Value Creation program and priorities, enhancing business objectives

• Oversee and drive the lifecycle of data science and AI projects and products, ensuring successful and timely delivery

• Establish, drive and manage Model Registry Framework

• Drive Model & Machine Learning Operations (MML Ops) automation

• Partner with various business units to identify and capitalize on opportunities for data-driven decision-making

• Present data-driven insights and strategic recommendations to senior management and key stakeholders

• Stay abreast of industry advancements and incorporate best practices and new technologies into data science processes.

• Ensure the accuracy, reliability, and ethical standards of data science and model outputs, excute respective code reviews

• Trains and mentors new or junior team members

• Uphold and enforce data governance policies, ensuring compliance with regulatory standards.

CORE ELEMENTS RELATED TO THIS ROLE:

We are currently hiring a hands-on Data Scientist at Principal Level within Enterprise Data & Analytics which is a part of Global Data, Digital and Technology unit at Takeda.
This person will respond directly to the Head of Data Science and Advanced AI in executing advanced data science, AI and modeling activities.
This is an individual contributor role, so you should be prepared to roll up your sleeves and flex a wide variety of skills.
You will be able to adapt quickly to shifting priorities, manage through ambiguity, while keeping focus on key implementation opportunities.

DIMENSIONS AND ASPECTS:

Technical/Functional (Line) Expertise (Breadth and depth of knowledge, application and complexity of technical knowledge)

• Strong expertise and experience in Generative AI (GenAI) / AI /Machine Learning algorithms, respective programming knowledge

• Strong expertise in GenAI/AI/ML best practices, e.g. code review

• 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 (Vision, strategy and business alignment, people management, communication, influencing others, managing change)

• 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 linking and influencing cross-functional stakeholder

• Influence best in class AI and data science culture, develop and elevate organizational performance

Decision-making and Autonomy (The capacity and authority to make organizational decisions, autonomy in decision-making, complexity of decisions, impact of decisions, problem-solving)

• Individual contributor role

• DOA in line with TMAP

Interaction (The span and nature of one’s engagement with others when performing one’s job, internal and external relationships)

• Role requires business partnership interface within and outside Enterprise Data & Analytics to ensure alignment for AI and data science priorities, roles, responsibilities and accountabilities

Innovation (The required level of scientific knowledge, knowledge sharing, innovation and risk taking)

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

Complexity (Products managed, mix of businesses, internal and/or external business environment, cultural considerations)

• Impact across the full portfolio of strategic products

• Ability to interface with international stakeholders and to connect internal and external data science and AI 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

EDUCATION, BEHAVIOURAL COMPETENCIES AND SKILLS: 

Education / Experience:

• Advanced degree required e.g. in Data Science, Computer Science, Engineering, Mathematics, Statistics, Physics, Economics or similar, Master's and PHD preferred

• For a Master's or a PhD, it is expected to have a minimum of 6 years of AI/Machine Learning/ Data Science experience in technology companies, Life Sciences, Pharma, Biotech, or relevant regulated industries (banking, insurance etc.). Minimum 8 years of production level experience after bachelor's degree.

• Advanced Machine Learning (ML) & Deep Learning (DL): Expertise in ML/DL algorithms, frameworks, and generative models

• Natural Language Processing (NLP) & GenAI: Proficiency in NLP techniques and state-of-the-art models for GenAI applications.

• Programming & Data Engineering: Strong coding skills in Python and R, data preprocessing, ETL, and handling big data with tools

• Cloud Computing & MML/MLOps: Experience with cloud platforms (AWS, Azure), containerization, model deployment, and MML/ MLOps practices, frameworks and automation

• Software Development & Ethics in AI: Proficient in software development best practices, version control (Git), algorithm optimization, and understanding of AI ethics and bias mitigation.

• Analytical Problem-Solving: Strong analytical and problem-solving abilities, focused on delivering actionable business solutions

• 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

• Professional/business level proficiency in both English and Japanese, with a global mindset and willingness to work in a multi-national environment.

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

ADDITIONAL INFORMATION:

This role requires onsite/hybrid presence and cannot be performed as remote only role.

Takeda Compensation and Benefits Summary:

• Allowances: Commutation, Housing, Overtime Work etc.

• Salary Increase: Annually, Bonus Payment: Twice a year

• Working Hours: Headquarters (Osaka/ Tokyo) 9:00-17:30, Production Sites (Osaka/ Yamaguchi) 8:00-16:45, (Narita) 8:30-17:15, Research Site (Kanagawa) 9:00-17:45

• Holidays: Saturdays, Sundays, National Holidays, May Day, Year-End Holidays etc. (approx. 123 days in a year)

• Paid Leaves: Annual Paid Leave, Special Paid Leave, Sick Leave, Family Support Leave, Maternity Leave, Childcare Leave, Family Nursing Leave.

• Flexible Work Styles: Flextime, Telework

• Benefits: Social Insurance, Retirement and Corporate Pension, Employee Stock Ownership Program, etc.

Important Notice concerning working conditions:

• It is possible the job scope may change at the company’s discretion.

• It is possible the department and workplace may change at the company’s discretion.

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