Senior Data Scientist - Agentic AI HybridData ScienceFull time New York, New York, United States Overview Description Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. As a Senior Data Scientist, you will apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next-generation advanced analytics engines and services. You will collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test. You will develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools. You will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results. Key Responsibilities - Serve as a resource for creating AI agents and RAG databases to solve problems. Develop AI Agent tools to automate the retrieval, wrangling, and analysis of data. - Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to prepare datasets, conduct analytics, and develop deployable solutions with guidance from more senior resources. - Able to analyze and prepare complex and new data sources and incorporate them into analytical solutions. - Collaborate with customers and key stakeholders on initiating ideas, performing design, analysis, and process improvement. - Develop and deploy AI and ML solutions on Google Cloud Platform. - Utilize massive data sources to craft business insights and features for innovative solutions. - Understand diverse data sources, both structured and unstructured. Requirements - - 7+ years of overall experience, 4+ years working as a GenAI Data Scientist. - Experience with Python from a functional programming paradigm, able to manage dependencies and virtual environments, along with version control in git - Machine learning and deep learning fundamentals, natural language processing (NLP), cloud computing, multi-agent systems understanding, data analysis, programming proficiency, and a grasp of ethical considerations in AI development. - Experience with agents frameworks (preferably Langchain). - Experience with Prompt engineering- Chatbots and virtual assistants, Image generation etc. - Experience with proprietary and/or open source LLMs. - Experience in prompt engineering. - Experience with RAG and Vector Databases Benefits Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

• Business Insight & Problem Definition: Partner closely with marketing and product teams to diagnose business challenges and define appropriate data metrics, analyses, and interpretations to drive strategic decisions. • Statistical Modeling: Define requirements for and lead the creation, monitoring, and iterative improvement of key statistical models used for marketing spend optimization and product growth. • Narrative & Visualization: Design clear, unambiguous narratives and data visualizations to communicate model outputs and analysis results to broad, non-technical audiences. • Rapid Prototyping: Independently prototype and test new insights, moving from hypothesis to rigorous validation with minimal mentorship. • Technical Consultation: Reason effectively about the strengths and weaknesses of different modeling approaches, selecting and iterating on combinations that suit specific marketing contexts.

• Build models that turn raw data into actionable insights • Build lead scoring models • Develop lookalike models to identify high-fit organizations • Turn messy data into usable, structured insights • Explore predictive approaches (e.g. classification, clustering, KNN, etc.)

About Jito Jito is an organization with the broad mandate to promote the adoption of Jito Network products, including JitoSOL, the largest DeFi protocol on Solana, and BAM, a platform for neutral block building on Solana. We are both extremely lean and relentlessly effective, and pride ourselves on having built a flat culture that prioritizes empowering multi-talented self starters to develop and pursue their own strategic vision. About the Role We're looking for a Data Scientist who thrives on turning messy, high-volume datasets into clear insight and who doesn't need to be pointed at the next problem. You'll work across our blockchain analytics and data infrastructure efforts - building models, running analyses, and surfacing findings that drive product and business decisions. This role is highly autonomous- you’ll independently chase leads, pursue lines of inquiry, and run with optimization opportunities, quantifying impact along the way. Jito is lean, fast, and executes at an elite level. Everyone is expected to have a material impact on the network. Crypto/blockchain domain knowledge is a plus, but what matters most is your ability to think critically, work fluently with data, operate independently, and pick up new domains fast. What You'll Do - Build dashboards, reports, and visualisations that make complex data accessible to technical and non-technical stakeholders - Design and execute quantitative analyses on large-scale blockchain and market datasets - Identify and scope new data streams that unlock deeper analysis across Jito's products - Develop statistical models and heuristics to detect patterns, anomalies, and trends across Jito's existing and emerging product suite - Collaborate with engineers and researchers to define metrics, improve complex systems, and drive product improvement - Identify new analytical opportunities and propose research directions independently What We're Looking For Must-haves - 3–5 years of professional experience in a data science, analytics, or quantitative research role - Strong SQL skills (ClickHouse / BigQuery / Snowflake) - you're comfortable writing complex queries across seriously large datasets and understand the tradeoffs between executing at different layers of the data stack - Proficient in Python for data analysis (pandas/polars, numpy, scipy, matplotlib/plotly) - Solid grounding in statistics and probability - you have the judgment to know when a problem demands rigorous statistical methods and when a simpler heuristic will do - Demonstrated ability to take ambiguous questions and turn them into structured analyses with actionable conclusions - Exceptional written and verbal communication - you can break down a complex problem space for someone who doesn't live in the data - Experience executing product data science on 0→1 products - shaping metrics, surfacing insight, and informing direction for products still finding their feet Nice-to-haves - Experience with blockchain data (Solana, Ethereum, or similar) - transaction-level, on-chain analytics - Public Dune dashboards or equivalent on-chain analysis you can point us to - Exposure to market microstructure, trading data, or DeFi protocol analytics - Background in experiment design (A/B testing, causal inference) - Surface and publish data-driven insights and communicate them clearly to broad, non-technical audiences - 1500+ chess Elo / Immortal in Dota 2 / Master+ in League / Grandmaster in SC2 / or equivalent proof you optimise things for fun