Referral Only- Data Scientist

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Job Description

As a Data Scientist , you will lead the development and implementation of advanced data engineering solutions to support the deployment and optimization of Generative AI models. Your role will involve leveraging your extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of General Artificial Intelligence (GenAI) applications.    Key Responsibilities 

• The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production generative AI systems. 
• Production level ML workloads for customers using Databricks platform, including end-to-end ML pipelines, training/inference optimization, integration with cloud-native services and MLOps
• Build and maintain data engineering solutions on cloud platforms using hyperscaler services. 
• Develop production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring
• Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes). 
• Understanding of indexing and vectorization to use with Generative AI prompt engineering. 
• Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models. 
• Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI. 
• Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.  

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Required Skills and Experience

• Bachelor's degree in computer science, data engineering, or a related field with 5+ years experience (Master's preferred). 
• Proven experience in data engineering, MLOps, ETL, and database management, QL and data manipulation languages. 
• Azure, Python, Java, or Scala. 
• data warehousing platforms (e.g., Databricks, Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
• highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets .

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The base compensation range for this role in the posted location is $110,000 to $135,000/YR

Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.

The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.

These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.

It is not typical for candidates to be hired at or near the top of the posted compensation range.

In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.

 

Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include: 

• Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave

• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
• Life and disability insurance
• Employee assistance programs