Senior Data Scientist

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Job Description:

The Future Begins Here:

At Takeda, we are leading digital evolution and global transformation. By building innovative solutions and future-ready capabilities, we are meeting the need of patients, our people, and the planet.

Bengaluru, the city, which is India’s epicenter of Innovation, has been selected to be home to Takeda’s recently launched Innovation Capability Center. We invite you to join our digital transformation journey. In this role, you will have the opportunity to boost your skills and become the heart of an innovative engine that is contributing to global impact and improvement.

At Takeda’s ICC we Unite in Diversity :

Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and abilities they bring to our company. We are continuously improving our collaborators journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team.

About The Role

• The Senior Data Scientist is responsible for performing complex data analysis to support business operations, with a primary focus on machine learning applications.
• This role involves developing data architectures, mining methodologies, and machine learning models to identify trends and insights from large datasets.
• By implementing advanced data science principles and techniques, this role helps drive informed business decisions and contributes significantly to Takeda’s mission.
  
  

ACCOUNTABILITIES:

• Collect and analyze large datasets from diverse sources to drive key business insights.
• Develop machine learning models, including supervised and unsupervised learning techniques, to predict and optimize business outcomes.
• Implement and optimize deep learning architectures and algorithms such as neural networks and reinforcement learning.
• Construct data architectures, models, and protocols to identify trends and insights.
• Create visualizations and dashboards to present data insights to stakeholders clearly and effectively.
• Work collaboratively with cross-functional teams to integrate machine learning insights into business strategies.
• Manage projects independently and provide guidance to junior professionals.
• Stay updated with the latest trends and advancements in machine learning and data science, applying them as needed.
• Implement MLOps best practices to streamline the deployment, monitoring, and lifecycle management of machine learning models in production environments using tools such as MLflow, Kubeflow, or Amazon SageMaker, Databricks.
• Collaborate with engineering teams to build scalable, reliable, and automated pipelines for machine learning workflows, leveraging tools like Airflow, Prefect, or AWS Step Functions for orchestration.
• Ensure robustness and compliance of ML solutions, focusing on CI/CD processes with tools like GitHub Actions, Jenkins, or Azure DevOps.
  
  

Skills And Qualifications

• Bachelor or higher educational background in mathematics, computer science, statistics, economics, or related fields.
• 5+ year of relevant experience.
• Proficient in programming languages such as Python and R, with a strong emphasis on machine learning libraries (e.g., scikit-learn, TensorFlow, Keras, PyTorch).
• Strong understanding of machine learning algorithms, including regression, classification, clustering, and dimensionality reduction techniques.
• Experience with deep learning frameworks and building complex neural network models.
• Expertise in natural language processing (NLP) techniques and applications.
• Proficiency in data visualization tools like Tableau or Power BI, and ability to communicate findings effectively.
• Strong data manipulation and database management skills, including SQL.
• Analytical thinking and problem-solving skills with the ability to develop innovative solutions.
• Strong business acumen and ability to translate machine learning insights into actionable business strategies.
• Excellent communication and interpersonal skills for effective collaboration with stakeholders.
• Knowledge of AutoML platforms and emerging technologies like generative AI.
• Hands-on experience with MLOps platforms (e.g., MLflow, Kubeflow, or SageMaker) for managing the end-to-end lifecycle of machine learning models.
  
  

Experience with containerization technologies (e.g., Docker) and orchestration frameworks (e.g., Kubernetes) for scalable deployment of ML models.

WHAT TAKEDA CAN OFFER YOU:

• Takeda is certified as a Top Employer, not only in India, but also globally. No investment we make pays greater dividends than taking good care of our people.
• At Takeda, you take the lead on building and shaping your own career.
• Joining the ICC in Bengaluru will give you access to high-end technology, continuous training and a diverse and inclusive network of colleagues who will support your career growth.
  
  

BENEFITS:

It is our priority to provide competitive compensation and a benefit package that bridges your personal life with your professional career. Amongst our benefits are

• Competitive Salary + Performance Annual Bonus
• Flexible work environment, including hybrid working
• Comprehensive Healthcare Insurance Plans for self, spouse, and children
• Group Term Life Insurance and Group Accident Insurance programs
• Employee Assistance Program
• Broad Variety of learning platforms
• Diversity, Equity, and Inclusion Programs
• Reimbursements – Home Internet & Mobile Phone
• Employee Referral Program
• Leaves – Paternity Leave (4 Weeks) , Maternity Leave (up to 26 weeks), Bereavement Leave (5 calendar days)
  
  

ABOUT ICC IN TAKEDA:

• Takeda is leading a digital revolution. We’re not just transforming our company; we’re improving the lives of millions of patients who rely on our medicines every day.
• As an organization, we are committed to our cloud-driven business transformation and believe the ICCs are the catalysts of change for our global organization.
  
  

Locations:

IND - Bengaluru

Worker Type:

Employee

Worker Sub-Type:

Regular

Time Type:

Full time