Associate - Platform Data Science

Job Description

Role Overview:You will be part of the BCN Data business expanding science capability area, specifically the PIT (PEG Innovation Team) Product Support. Your main responsibility will be to support the Beta production of AI applications for the Private Equity Group (PEG) as part of Bains Due Diligence 2030 (DD2030) initiative. A significant part of your work will involve Generative AI applications, focusing on innovation in the private equity space. Additionally, you may contribute to broader PIT automation initiatives aimed at streamlining processes and enhancing efficiency across various investment lifecycle stages. Your role will involve translating business objectives into data and analytics solutions, leveraging Gen AI skills to improve data quality, building and deploying machine learning models, implementing NLP models, collaborating with engineering teams, and staying updated on AI/ML technologies and best practices.Key Responsibilities:- Translate business objectives into data and analytics solutions using appropriate data engineering, analytics, visualization & Gen AI applications- Design and create repeatable analytical solutions to enhance data quality- Build and deploy machine learning models using Scikit-Learn for predictive analytics tasks- Implement and fine-tune NLP models with Hugging Face for complex language processing challenges- Collaborate with engineering team members to turn PoC methods into repeatable data pipelines- Assist in creating and documenting standard operating procedures and knowledge base of data methods- Stay updated on new developments in AI/ML technologies, particularly in LLMs and generative AIQualifications Required:- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Applied Mathematics, Econometrics, Statistics, Physics, Market Research, or related field preferred- 3-5 years of experience in data science & data engineering- Hands-on experience with AI/GenAI tools such as Scikit-Learn, LangChain, and Hugging Face- Proficiency in data wrangling in R or Python- Proficiency in SQL, familiarity with NoSQL data stores is a plus- Experience designing and developing RESTful and GraphQL APIs- Familiarity with MLOps practices- Experience with Git and modern software development workflow- Experience with containerization such as Docker/Kubernetes- Agile way of working and tools (Jira, Confluence, Miro)- Strong interpersonal and communication skills- Ability to explain and discuss Gen AI and Data Engineering technicalities to a business audience- Experience with Microsoft Office suite is preferred Role Overview:You will be part of the BCN Data business expanding science capability area, specifically the PIT (PEG Innovation Team) Product Support. Your main responsibility will be to support the Beta production of AI applications for the Private Equity Group (PEG) as part of Bains Due Diligence 2030 (DD2030) initiative. A significant part of your work will involve Generative AI applications, focusing on innovation in the private equity space. Additionally, you may contribute to broader PIT automation initiatives aimed at streamlining processes and enhancing efficiency across various investment lifecycle stages. Your role will involve translating business objectives into data and analytics solutions, leveraging Gen AI skills to improve data quality, building and deploying machine learning models, implementing NLP models, collaborating with engineering teams, and staying updated on AI/ML technologies and best practices.Key Responsibilities:- Translate business objectives into data and analytics solutions using appropriate data engineering, analytics, visualization & Gen AI applications- Design and create repeatable analytical solutions to enhance data quality- Build and deploy machine learning models using Scikit-Learn for predictive analytics tasks- Implement and fine-tune NLP models with Hugging Face for complex language processing challenges- Collaborate with engineering team members to turn PoC methods into repeatable data pipelines- Assist in creating and documenting standard operating procedures and knowledge base of data methods- Stay updated on new developments in AI/ML technologies, particularly in LLMs and generative AIQualifications Required:- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Applied Mathematics, Econometrics, Statistics, Physics, Market Research, or related field preferred- 3-5 years of experience in data science & data engineering- Hands-on experience with AI/GenAI tools such as Scikit-Learn, LangChain, and Hugging Face- Proficiency in data wrangling in R or Python- Proficiency in SQL, familiarity with NoSQL data stores is a plus- Experience designing and developing RESTful and GraphQL APIs- Familiarity with MLOps practices- Experience with Git and modern software development workflow- Experience with containerization such as Docker/Kubernetes- Agile way o

Keyskills :
Data ScienceData EngineeringNLPMachine LearningSQLNoSQLGitDockerKubernetesAgileJiraConfluenceMicrosoft OfficeGenAIScikitLearnHugging FaceRESTful APIGraphQL APIMLOps