Senior Data Scientist (NYC)

TWG Global AI • New York, NY

3d • $190,000 - $200,000 • Onsite

About The Position

At TWG Group Holdings, LLC ("TWG Global"), we drive innovation and business transformation across a range of industries, including financial services, insurance, technology, media, and sports, by leveraging data and AI as core assets. Our AI-first, cloud-native approach delivers real-time intelligence and interactive business applications, empowering informed decision-making for both customers and employees. We prioritize responsible data and AI practices, ensuring ethical standards and regulatory compliance. Our decentralized structure enables each business unit to operate autonomously, supported by a central AI Solutions Group, while strategic partnerships with leading data and AI vendors fuel game-changing efforts in marketing, operations, and product development. You will collaborate with management to advance our data and analytics transformation, enhance productivity, and enable agile, data-driven decisions. By leveraging relationships with top tech startups and universities, you will help create competitive advantages and drive enterprise innovation. At TWG Global, your contributions will support our goal of sustained growth and superior returns, as we deliver rare value and impact across our businesses. The Role As a Senior Associate, Data Scientist, you'll work alongside experienced data scientists and ML engineers to design, develop, and apply data-driven models and analyses that deliver measurable business value. Reporting to the Executive Director of AI Science, you'll gain hands-on experience working on impactful projects across the enterprise, applying advanced analytics and machine learning to areas such as financial services, insurance, and operations optimization. This is a high-growth opportunity for someone with early industry experience (or strong academic grounding) in data science and applied statistics, eager to deepen their expertise and grow within a dynamic AI team working at the frontier of applied analytics and machine learning.

Requirements

• 5+ years of experience applying data science or advanced analytics in a professional setting.
• Solid understanding of statistical modeling, machine learning fundamentals, and experimental design.
• Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting.
• Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow).
• Strong experience with SQL and data manipulation across large datasets.
• Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI).
• Excellent problem-solving skills, eagerness to learn, and ability to work in fast-paced, evolving environments.
• Strong written and verbal communication skills, with the ability to translate technical findings into business recommendations.
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, or another quantitative discipline.

Nice To Haves

• Hands-on experience with Palantir platforms (Foundry, AIP, Ontology), including developing analytical workflows and deploying insights within enterprise environments.
• PhD in Data Science, Statistics, Computer Science, or a related quantitative field.
• Publications in top data science / ML conferences or journals (e.g., NeurIPS, ICML, KDD, ACL, or similar).
• Open-source contributions to the data science or ML community (libraries, notebooks, packages, or tutorials).
• Experience presenting research or applied work at meetups, workshops, or industry conferences.
• Familiarity with vector databases (FAISS, Pinecone, Milvus, Weaviate) and LLM application frameworks.
• Cloud or AI/ML certifications (e.g., AWS Machine Learning Specialty, Google Professional Data Engineer, Azure AI Engineer) are a plus.

Responsibilities

• Contribute to the development of predictive and statistical models addressing business-critical challenges across diverse domains.
• Conduct exploratory data analysis, feature engineering, and hypothesis testing to uncover patterns and support model development.
• Collaborate with senior data scientists and ML engineers to refine models, improve accuracy, and enhance interpretability.
• Support the design and evaluation of experiments and A/B tests, ensuring rigorous measurement of impact.
• Clean, transform, and prepare data from diverse sources, ensuring high-quality datasets for analysis.
• Build dashboards, reports, and visualizations that communicate insights clearly to technical and non-technical stakeholders.
• Stay current with emerging data science methods and tools (e.g., generative AI, LLMs, causal inference) and apply them through prototyping.
• Contribute to the team's knowledge base by documenting workflows and sharing best practices.

Benefits

• Work at the forefront of AI/ML innovation in life insurance, annuities, and financial services.
• Drive AI transformation for some of the most sophisticated financial entities.
• Competitive compensation, benefits, future equity options, and leadership opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level