Data Scientist

Data Scientist – GenAI & Machine Learning Location: Newark, NJ (Hybrid – 3 days/week onsite) Employment Type: W2 Only (No C2C or 1099) Rate: $55–$65/hr on W2 (depending on experience) Work Authorization: Must have permanent work authorization to work in the U.S. Position Type: Contract-to-Hire Role Overview As a Data Scientist on the Data Science Team, you will collaborate with Machine Learning Engineers, Data Engineers, Business Leaders, and cross-functional stakeholders to design and implement GenAI and machine learning models. Your work will directly enhance advisor experiences, enable lead scoring, and support revenue growth. This role combines deep technical execution with strategic thinking and product integration, offering meaningful business impact through AI innovation. The position is hybrid and requires a regular on-site presence at the Newark, NJ office (typically 3 days per week). Specific on-site expectations will be determined by your manager. Key Responsibilities • Provide technical leadership on high-impact data science initiatives focused on sales enablement and advisor experience • Design, train, and evaluate ML/AI models, including lead scoring and GenAI solutions • Identify new business opportunities through AI, proposing novel use cases and solutions • Manage and mentor team members in AI/ML techniques, model development, testing, and deployment • Communicate model concepts and findings clearly and effectively, both verbally and in writing • Oversee vendor contributions when necessary in support of model development • Implement CI/CD best practices to support model deployment on the company’s AI/ML platform • Stay current on emerging AI technologies and embed innovation into daily practice • Work on complex and unique problems requiring evaluation of abstract variables • Utilize tools and languages such as Python, SQL, AWS, and JIRA • Work with modern GenAI tools including LLMs, RAG, LangChain, LangGraph, and Agentic AI concepts Required Skills and Experience • Background in Applied Statistics, Computer Science, Engineering, or a related discipline • Industry experience developing and delivering advanced AI/ML and statistical solutions • Ability to lead small teams independently and build diverse, high-performing environments • Experience influencing stakeholders and driving AI/ML adoption across functions • Agile development and product management experience, including Test-Driven Development (TDD) • Sound business acumen with knowledge of decision-making processes and operational strategy • Proven experience managing and mentoring data science teams • Strong problem solving, communication, collaboration, and stakeholder engagement skills Technical Expertise Machine Learning & AI • Deep understanding of machine learning theory and its practical application • Expertise in building, training, testing, and monitoring ML models • Familiarity with traditional ML techniques (e.g., unsupervised learning, XGBoost) and LLMs (e.g., OpenAI, Claude) Model Deployment & MLOps • CI/CD/CT pipeline experience (e.g., Jenkins, CloudBees, Harness) • Exposure to tools like AWS SageMaker and Azure AI agentic infrastructure • A/B testing frameworks and model lifecycle management Data Engineering & Visualization • Skilled in data acquisition using APIs and SQL • Data transformation and visualization using Python and SQL • Ability to analyze structured and unstructured data for insights and trends Database Management • Understanding of relational database structures, schemas, and key relationships • Experience working across multiple environments, including cloud (AWS preferred) Why You’ll Love This Role Join a culture where your voice is heard and your expertise is valued. Every day, your contributions will improve experiences for advisors and customers. You’ll have access to meaningful learning opportunities to sharpen both your technical and leadership skills—while working in a rock-solid, forward-thinking organization that’s building for the future.