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Essential Responsibilities:
Expected Qualifications:
Key Responsibilities:
Research and develop large-scale foundation models, including continuous pre-training, supervised fine-tuning, and alignment techniques
Design novel architectures and training methodologies for domain-specific language models in financial services
Build scalable ML pipelines for foundation model training, evaluation, and deployment at enterprise scale
Conduct rigorous experimentation and benchmarking to ensure model quality, safety, and performance
Deploy foundation models into production environments to drive business insights and enhance customer experiences
Collaborate with cross-functional teams to identify high-impact use cases and translate research into practical solutions
Stay current with latest developments in LLM and LLM-Agent research and contribute to the broader AI/ML community through publications and open-source contributions
Mentor junior researchers and contribute to technical strategy for foundation model initiatives
Preferred Qualifications:
PhD in Computer Science, Machine Learning, AI, or related field with focus on large language models and LLM Agent
1-3+ years of hands-on experience training and deploying large-scale language models (7B+ parameters)
Deep expertise in transformer architectures, attention mechanisms, and modern training techniques
Experience with distributed training frameworks (PyTorch, JAX, DeepSpeed, etc.)
Strong background in NLP, deep learning, and statistical machine learning
Proven track record of research publications in top-tier venues (NeurIPS, ICML, ACL, etc.)
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $169,500 to $291,500
Our Benefits:
Any general requests for consideration of your skills, please
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Embark on a future with an international pharmaceuticals company, contributing your creative energy to high-impact projects from the moment you arrive through the course of this 12 week experience. You will take part in meaningful work and real-life projects that will help you grow both professionally and personally throughout the program.
Tasks & responsibilities
The internal career site is available from your home network as well. If you have trouble accessing your EC account, please contact your local HR/IT partner.

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Essential Responsibilities:
Expected Qualifications:
Additional Responsibilities & Preferred Qualifications
-Strong analytical and problem-solving mindset, with a degree in a quantitative field such as Data Science, Computer Science, Engineering, Statistics, Mathematics, Economics, or a related discipline
-4+ years of experience in Product Data Science, including A/B testing and experimentation, advanced analytics, and applied machine learning-Advanced proficiency in SQL and Python, with expertise in working with large-scale, complex datasets to derive actionable insights-Hands-on experience with modern data tools and platforms such as Jupyter Notebooks, BigQuery, Teradata, Hadoop, or Hive is highly desirable
-Exceptional communication and data storytelling skills, with the ability to distill complex findings for both technical and non-technical audiences and influence cross-functional decision-making-Prior work experience inanalytics space would be highly valued
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $123,500 to $212,850
Our Benefits:
Any general requests for consideration of your skills, please

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Job Description:
Minimum Requirements: Master’s degree, or foreign equivalent, in Data Science, Data Analytics, or a closely related field plus two years of experience in the job offered or a related occupation.
Special Skill Requirements:
Performing scalable analysis using R and Python [2 years]
Database query languages including SQL [2 years]
Statistical analysis, including descriptive statistics, correlation, regression, or confidence intervals [2 years]
Developing relevant metrics or KPIs to measure performance by product teams [2 years]
Debugging and monitoring for production services [2 years]
Experimentation techniques including A/B testing or simulation [1.5 years]
Quantitative modeling, including machine learning models, time series forecasting or casual impact analyses [1.5 years]
Data analysis or machine learning systems [2 years]
Additional Responsibilities & Preferred Qualifications
Salary:$174,304.00-243,500.00per annum. 40 hours per week; M-F, 9:00 a.m. to 5:00 p.m.
Must be legally authorized to work in the U.S. without sponsorship.
Our Benefits:
Any general requests for consideration of your skills, please

Share
Essential Responsibilities:
Expected Qualifications:
Our Benefits:
Any general requests for consideration of your skills, please

Share
Essential Responsibilities:
Expected Qualifications:
Preferred Qualification:
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $152,500 to $262,350
Our Benefits:
Any general requests for consideration of your skills, please

Share
Essential Responsibilities:
Expected Qualifications:
Additional Responsibilities & Preferred Qualifications
Partner withProduct, Engineering, and Finance
causal inference and forecasting models
Design and operationalizeexperimentation frameworksto improve product performance and user engagement.
Develop andmaintainreusable data pipelines, embeddings, and feature librariesto accelerate model development.
Communicate insights and recommendations clearly to leadership, influencing strategic direction across teams.
expertiseincausal inference,experimentation, andmodel-driven decision-making.
inPython, SQL, and statisticalmodelingframeworks(e.g.,XGBoost, regression, time series, DML).
Experience in cloud environments (AWS, GCP) and analytics tools (Tableau,PySpark).
Strong stakeholder management and ability to communicate insights to non-technical audiences.
Experience leadingexperimentation and measurement strategiesin large-scale tech environments.
Experience in setting upAgentic workflowsfor automating data requests and root cause analysis
Background inproduct analytics and marketing measurement.
cross-functional collaborationwith product, engineering, and business stakeholders.
Experience mentoring data scientists and driving adoption of data-driven decision-making practices.
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $152,500 to $262,350
Our Benefits:
Any general requests for consideration of your skills, please

Share
Essential Responsibilities:
Expected Qualifications:
Key Responsibilities:
Research and develop large-scale foundation models, including continuous pre-training, supervised fine-tuning, and alignment techniques
Design novel architectures and training methodologies for domain-specific language models in financial services
Build scalable ML pipelines for foundation model training, evaluation, and deployment at enterprise scale
Conduct rigorous experimentation and benchmarking to ensure model quality, safety, and performance
Deploy foundation models into production environments to drive business insights and enhance customer experiences
Collaborate with cross-functional teams to identify high-impact use cases and translate research into practical solutions
Stay current with latest developments in LLM and LLM-Agent research and contribute to the broader AI/ML community through publications and open-source contributions
Mentor junior researchers and contribute to technical strategy for foundation model initiatives
Preferred Qualifications:
PhD in Computer Science, Machine Learning, AI, or related field with focus on large language models and LLM Agent
1-3+ years of hands-on experience training and deploying large-scale language models (7B+ parameters)
Deep expertise in transformer architectures, attention mechanisms, and modern training techniques
Experience with distributed training frameworks (PyTorch, JAX, DeepSpeed, etc.)
Strong background in NLP, deep learning, and statistical machine learning
Proven track record of research publications in top-tier venues (NeurIPS, ICML, ACL, etc.)
Travel Percent:
The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .
The US national annual pay range for this role is $169,500 to $291,500
Our Benefits:
Any general requests for consideration of your skills, please
These jobs might be a good fit