

HireTalent - Diversity Staffing & Recruiting Firm
Sr. Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr. Data Scientist with a hybrid work arrangement in Newark, NJ, offering a competitive pay rate. Key skills include Python, SQL, AWS, and experience with machine learning models. Agile methodology and leadership experience are required. Contract length is unspecified.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
October 31, 2025
π - Duration
Unknown
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Newark, NJ
-
π§ - Skills detailed
#Deployment #Monitoring #AWS (Amazon Web Services) #Unsupervised Learning #Database Design #A/B Testing #Agile #Database Management #Programming #Data Engineering #Python #Data Science #ML (Machine Learning) #Visualization #Scala #Jenkins #SQL (Structured Query Language) #AWS SageMaker #Cloudbees #AI (Artificial Intelligence) #Cloud #Supervised Learning #Leadership #Automation #Azure #Langchain #Continuous Deployment #Matplotlib #Model Deployment #"ETL (Extract #Transform #Load)" #Databases #Jira #SageMaker
Role description
Description: Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? β all while growing your skills and advancing your profession at one of the worldβs leading financial services institutions.
As a Director, Data Scientist on/in the US Businesses Data Science Team you will partner with Machine Learning Engineers, Data Engineers, Business Leaders and other professionals to build GenAI and ML models to improve advisor experience, perform lead scoring, and increase sales revenue. You will implement AI and machine learning models that will deliver stability, scalability and integration with other advisor products and services. You will implement capabilities to solve sophisticated business problems, deploy innovative products, services and experiences to delight our customers! In addition to deep technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership attitude and a continuous learning focus to all that you do.
The current work arrangement for this position is Hybrid (Newark, NJ) and requires your on-site presence on a recurring weekly basis as determined by your business. Your manager will provide additional details relative to the specific number of days you are expected to be on-site.
Here is what you can expect in a typical day:
β’ Provide deep technical leadership to a portfolio of high-impact data science initiatives involving sales and advisor experience. Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery. Remove complex technical impediments
β’ Leverage your experience and skills to identify new opportunities where data science and AI can improve experiences, gain efficiencies, and generate sales.
β’ Manage team members in AI/ML and model development, testing, training, and tuning. Apply hands-on experience to ensuring best-in-class model development. Mentor team members in technical skill development and product ownership.
β’ Communicate clearly and concisely, in writing and verbally, all facets of model design and development. Continuously look for insights in models developed and generate new ideas for model improvement.
β’ Manage external vendors in the execution of parts of the data science development process as needed.
β’ Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code on Prudentialβs AI/ML platform.
β’ Bring a deep understanding of relevant and emerging technologies, give technical direction to team members and embed learning and innovation in the day-to-day.
β’ Work on significant and unique issues where analysis of situations or data requires an evaluation of intangible variables and may impact future concepts, products or technologies.
β’ Familiarity with Python, SQL, AWS, and JIRA.
β’ Familiarity with LLMs, deployment of LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts.
Technical Skills & Tools:
β’ Machine Learning & AI: Traditional ML models (unsupervised learning, XGBoost), Large Language Models (OpenAI, Claude)
β’ Model Deployment: CI/CD/CT pipelines (Jenkins, CloudBees, Harness), AWS SageMaker, AWS/Azure Agentic AI infrastructure, A/B testing
β’ Programming Languages: Python, SQL
β’ Data Acquisition & Transformation: APIs, SQL, Python
β’ Data Visualization Tools: Python (e.g., Matplotlib, Seaborn, etc.)
β’ Database Management: Database design, schemas, primary/foreign keys, cloud databases (AWS)
β’ Development Methodologies: Agile, Test-Driven Development (TDD)
Description: Are you interested in building capabilities that enable the organization with innovation, speed, agility, scalability and efficiency? β all while growing your skills and advancing your profession at one of the worldβs leading financial services institutions.
As a Director, Data Scientist on/in the US Businesses Data Science Team you will partner with Machine Learning Engineers, Data Engineers, Business Leaders and other professionals to build GenAI and ML models to improve advisor experience, perform lead scoring, and increase sales revenue. You will implement AI and machine learning models that will deliver stability, scalability and integration with other advisor products and services. You will implement capabilities to solve sophisticated business problems, deploy innovative products, services and experiences to delight our customers! In addition to deep technical expertise and experience, you will bring excellent problem solving, communication and teamwork skills, along with agile ways of working, strong business insight, an inclusive leadership attitude and a continuous learning focus to all that you do.
The current work arrangement for this position is Hybrid (Newark, NJ) and requires your on-site presence on a recurring weekly basis as determined by your business. Your manager will provide additional details relative to the specific number of days you are expected to be on-site.
Here is what you can expect in a typical day:
β’ Provide deep technical leadership to a portfolio of high-impact data science initiatives involving sales and advisor experience. Identify the optimal sets of data, models, training, and testing techniques required for successful product delivery. Remove complex technical impediments
β’ Leverage your experience and skills to identify new opportunities where data science and AI can improve experiences, gain efficiencies, and generate sales.
β’ Manage team members in AI/ML and model development, testing, training, and tuning. Apply hands-on experience to ensuring best-in-class model development. Mentor team members in technical skill development and product ownership.
β’ Communicate clearly and concisely, in writing and verbally, all facets of model design and development. Continuously look for insights in models developed and generate new ideas for model improvement.
β’ Manage external vendors in the execution of parts of the data science development process as needed.
β’ Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code on Prudentialβs AI/ML platform.
β’ Bring a deep understanding of relevant and emerging technologies, give technical direction to team members and embed learning and innovation in the day-to-day.
β’ Work on significant and unique issues where analysis of situations or data requires an evaluation of intangible variables and may impact future concepts, products or technologies.
β’ Familiarity with Python, SQL, AWS, and JIRA.
β’ Familiarity with LLMs, deployment of LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts.
Technical Skills & Tools:
β’ Machine Learning & AI: Traditional ML models (unsupervised learning, XGBoost), Large Language Models (OpenAI, Claude)
β’ Model Deployment: CI/CD/CT pipelines (Jenkins, CloudBees, Harness), AWS SageMaker, AWS/Azure Agentic AI infrastructure, A/B testing
β’ Programming Languages: Python, SQL
β’ Data Acquisition & Transformation: APIs, SQL, Python
β’ Data Visualization Tools: Python (e.g., Matplotlib, Seaborn, etc.)
β’ Database Management: Database design, schemas, primary/foreign keys, cloud databases (AWS)
β’ Development Methodologies: Agile, Test-Driven Development (TDD)





