Position:
Data Scientist
Company:
Zimmer Biomet
Location:
Bangalore, Karnataka, India
Job Type:
Full Time
Job Mode:
Hybrid (3 Days in Office)
Job Requisition ID:
10046
Years of Experience:
0 to 3 Years (Estimated based on role requirements)
Company Description
Zimmer Biomet is a globally recognized medical technology organization with a legacy spanning nearly a century.
The company is dedicated to improving patient mobility and enhancing quality of life through innovative healthcare solutions.
Its products and technologies are widely used across hospitals, healthcare institutions, and medical facilities around the world.
The organization has established itself as a trusted leader in orthopedic and musculoskeletal healthcare technologies.
Every few seconds, a patient somewhere in the world benefits from a Zimmer Biomet product or technological solution, demonstrating the company's large global impact.
Innovation remains one of the central pillars of the organization’s long term strategy.
The company invests heavily in technology, research, analytics, digital transformation, and artificial intelligence to improve healthcare outcomes.
Zimmer Biomet promotes a culture that values collaboration, accountability, inclusion, and continuous improvement.
Employees are encouraged to contribute ideas that help solve meaningful healthcare challenges.
The company supports professional growth through learning opportunities, development programs, mentorship initiatives, and exposure to global projects.
Team members benefit from employee resource groups that help foster diversity and inclusion.
Zimmer Biomet places significant emphasis on employee wellbeing and offers various wellness related initiatives.
Recognition programs are designed to reward performance, innovation, teamwork, and contributions to organizational goals.
The organization encourages employees to bring their authentic selves to work and promotes a workplace built on respect and equal opportunity.
Flexible working arrangements are offered where possible to support work life balance.
The company continues to invest in advanced technologies including data science, machine learning, automation, and artificial intelligence.
Digital transformation initiatives play an important role in supporting business functions across procurement, sourcing, operations, supply chain, and healthcare innovation.
Employees gain exposure to global stakeholders and cross functional teams.
The company maintains a strong commitment to ethical business practices and responsible innovation.
By joining Zimmer Biomet, professionals become part of a mission driven organization focused on improving lives through technology and healthcare innovation.
Profile Overview
Zimmer Biomet is seeking a Data Scientist who possesses strong expertise in Natural Language Processing and Large Language Models.
The position is focused on leveraging artificial intelligence to transform procurement and strategic sourcing operations.
The successful candidate will work with both commercial SaaS based language models and self hosted open source language models.
The role requires active involvement in building practical AI driven solutions rather than purely theoretical research.
A major focus will be placed on extracting value from large volumes of unstructured business data.
Examples of such data include supplier communications, procurement documents, contracts, market intelligence reports, specifications, and sourcing related content.
The individual will develop systems capable of converting raw information into meaningful insights that can support business decision making.
Responsibilities include creating intelligent applications that help improve sourcing effectiveness and procurement efficiency.
The role combines elements of machine learning, data science, NLP engineering, prompt engineering, and AI solution development.
The candidate will participate in designing, testing, evaluating, and deploying advanced NLP solutions.
Significant collaboration with sourcing and procurement teams will be required.
Business requirements must be translated into practical AI solutions capable of generating measurable value.
The position involves experimentation with emerging AI technologies and modern language model architectures.
The professional will contribute to internal AI innovation efforts and support adoption of best practices across teams.
Strong communication skills are essential because the role requires explaining technical concepts to business stakeholders.
The position offers opportunities to work on cutting edge AI use cases involving retrieval augmented generation and domain specific language models.
Exposure to large scale enterprise data environments will be a key component of daily responsibilities.
The individual will help establish scalable frameworks that can be expanded across multiple procurement functions.
This role provides an opportunity to work at the intersection of healthcare technology, procurement transformation, and artificial intelligence.
It is an excellent position for professionals interested in applying modern AI techniques to solve real world business challenges.
Qualifications
Candidates should possess a strong educational and practical background in Data Science, Machine Learning, Artificial Intelligence, Computer Science, Analytics, or related disciplines.
Demonstrated understanding of Natural Language Processing methodologies is highly important.
Applicants should be comfortable working with tokenization techniques and text preprocessing workflows.
Experience with vector embeddings and semantic search approaches is desirable.
Knowledge of transformer architectures and modern language model frameworks is expected.
Familiarity with sequence modeling techniques and deep learning concepts will be beneficial.
Exposure to parameter efficient fine tuning approaches such as LoRA and QLoRA is preferred.
Hands on experience working with Large Language Models is an important requirement.
Candidates should understand prompt design strategies and methods for improving model responses.
Experience evaluating model performance using appropriate metrics and testing frameworks is valuable.
Strong Python programming skills are required.
Applicants should have experience using machine learning and NLP libraries.
Familiarity with frameworks such as PyTorch, Hugging Face, and spaCy is advantageous.
Ability to work with large scale unstructured text datasets is expected.
Candidates should understand challenges associated with data quality and preprocessing.
Knowledge of model limitations, fairness considerations, and bias related issues is important.
Familiarity with retrieval augmented generation workflows is considered a strong advantage.
Understanding vector databases and embedding search technologies can help candidates succeed in this position.
Experience deploying machine learning models in enterprise environments is beneficial.
Knowledge of APIs and production deployment workflows will be valuable.
Exposure to MLOps concepts such as model monitoring and lifecycle management is preferred.
Understanding reproducible machine learning pipelines is important.
Candidates should possess strong analytical thinking and problem solving capabilities.
Communication skills should be strong enough to interact with both technical and non technical audiences.
The ability to understand business requirements and translate them into technical solutions is highly desirable.
Teamwork and collaboration skills are essential because the role involves extensive cross functional interaction.
Curiosity about emerging AI technologies and willingness to continuously learn new tools will contribute to success.
Experience with procurement, sourcing, contract analysis, or supply chain related datasets would be beneficial.
Candidates should be capable of working independently while also contributing effectively within collaborative environments.
Strong organizational skills and attention to detail will help ensure successful project execution.
Key Responsibilities
NLP and Large Language Model Development
Design NLP pipelines capable of processing large amounts of unstructured textual information.
Build classification systems that automatically categorize documents and business content.
Develop information extraction frameworks for identifying relevant details from contracts and procurement records.
Create text summarization solutions that improve accessibility of lengthy business documents.
Implement entity recognition systems to identify suppliers, products, contractual terms, and business entities.
Build similarity search capabilities for efficient information retrieval.
Design and optimize prompt engineering strategies.
Develop retrieval augmented generation architectures to improve model accuracy.
Evaluate model performance using structured testing approaches.
Improve model efficiency in terms of speed, memory consumption, and operational costs.
Fine tune open source language models for domain specific applications.
Support deployment and maintenance of enterprise AI solutions.
Strategic Sourcing and Procurement Applications
Build AI solutions that enhance supplier analysis and benchmarking activities.
Create systems that assist in supplier comparison and evaluation.
Support contract review and clause analysis initiatives.
Develop tools capable of extracting metadata from contractual documents.
Enhance spend categorization and procurement data enrichment efforts.
Improve RFQ and RFP generation processes using AI.
Assist stakeholders in evaluating procurement responses.
Develop solutions that provide supplier intelligence insights.
Support market intelligence gathering and analysis activities.
Transform sourcing challenges into AI driven business solutions.
Data Engineering and MLOps
Work with structured and unstructured datasets from various sources.
Design data processing workflows for enterprise scale environments.
Develop reproducible model training pipelines.
Support model evaluation and validation processes.
Collaborate on deployment mechanisms including APIs and internal tools.
Improve maintainability of AI solutions.
Ensure traceability and governance standards are maintained.
Contribute to scalable machine learning infrastructure initiatives.
Stakeholder Collaboration
Partner closely with sourcing professionals and procurement teams.
Collaborate with analytics specialists and domain experts.
Understand operational challenges and business objectives.
Present findings and recommendations to stakeholders.
Explain model outputs and limitations clearly.
Support organizational AI adoption initiatives.
Contribute to AI governance and best practice development.
Participate in cross functional innovation projects.
Additional Information
The role is based in Bangalore, India.
Employees are expected to work in a hybrid model with office attendance three days per week.
The position sits within the Supply Chain function.
The opportunity offers exposure to advanced artificial intelligence initiatives.
Professionals will gain experience with both commercial and open source language models.
The role provides practical experience in enterprise NLP implementation.
Employees will contribute to strategic procurement transformation programs.
Exposure to real world AI deployment environments will be significant.
The position offers opportunities to collaborate with international teams and stakeholders.
Candidates will work on impactful projects that influence sourcing and procurement decisions.
The organization encourages innovation and experimentation with emerging technologies.
Team members will gain experience working with large scale enterprise data environments.
Continuous learning and professional growth are strongly supported.
Exposure to modern AI architectures and enterprise deployment frameworks will help strengthen technical expertise.
The role combines business understanding with technical execution.
Professionals will contribute to improving operational efficiency through intelligent automation.
Experience gained in this position can support long term career growth in Data Science, AI Engineering, NLP Engineering, and Machine Learning.
The organization values diversity, inclusion, collaboration, and employee wellbeing.
Employees have opportunities to contribute ideas that shape future AI initiatives.
This position represents a strong opportunity for professionals seeking meaningful work at the intersection of healthcare technology, procurement transformation, and artificial intelligence.
Please click here to apply.
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