• 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

Data scientists at Thoughtworks are responsible for leading and executing data science projects. They employ their profound expertise in statistics, modeling, machine learning algorithms and data mining methodologies. They integrate this expertise with a comprehensive understanding of related domains to render business value and illuminate data-driven insights, facilitating clear and effective decision-making processes. Their responsibilities encompass devising strategies, executing plans, operationalizing solutions and articulating the tangible business outcomes achieved. Collaborating with cross-functional teams is pivotal, as they adeptly convey their discoveries to both technical and non-technical stakeholders. They stay up-to-date with industry advancements, ensure data quality and security, and provide guidance to junior team members. As a data scientist at Thoughtworks, you'll work on a range of projects and leverage deep technical knowledge to solve complex business problems. Job responsibilities - You will lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration. - You will collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning. - You will be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues. - You will design, develop and implement data science strategies that drive measurable business results. - You will design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action. - You will use quality metrics to select machine learning models that will be deployed in the production environment. - You will communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind. - You will contribute to the growth of the data science community along with promoting a culture of data literacy within the organization. - You will address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility). - You will work with CD4ML practices and data versioning tools. Job qualifications Technical Skills - You have experience with databricks - You have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects. - You understand about Gen/AI and LLMs - You have practical knowledge of Google Cloud Platform (GCP) and its core services. - You have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test. - You gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity. - You have experience with BigQuery for data modeling, querying, and performance optimization. - You develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes. - You evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability. - You interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations. - You ensure compliance with data privacy regulations and ethical standards when handling sensitive information. - You have practical knowledge of Machine Learning (ML) concepts and workflows. - Advanced English is required Professional Skills - You understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way. - You are resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives. - You don’t shy away from risks or conflicts, instead you take them on and skillfully manage them. - You are eager to coach, mentor and motivate others and you aspire to influence teammates to take positive action and accountability for their work. - You enjoy influencing others and always advocate for technical excellence while being open to change when needed. - You are a proven leader with a track record of encouraging teammates in their professional development and relationships. - Cultivating strong partnerships comes naturally to you; You understand the importance of relationship building and how it can bring new opportunities to our business. Other things to know Learning & Development There is no one-size-fits-all career path at Thoughtworks: however you want to develop your career is entirely up to you. But we also balance autonomy with the strength of our cultivation culture. This means your career is supported by interactive tools, numerous development programs and teammates who want to help you grow. We see value in helping each other be our best and that extends to empowering our employees in their career journeys. About Thoughtworks Thoughtworks is a dynamic and inclusive community of bright and supportive colleagues who are revolutionizing tech. As a leading technology consultancy, we’re pushing boundaries through our purposeful and impactful work. For 30+ years, we’ve delivered extraordinary impact together with our clients by helping them solve complex business problems with technology as the differentiator. Bring your brilliant expertise and commitment for continuous learning to Thoughtworks. Together, let’s be extraordinary. #LI-Onsite See here our AI policy.

• Investigate FP/FN and product escalations from PS and SOCC related to BMP and Account Protector. • Perform deep-dive analysis on traffic patterns, request signatures, behavioral signals, and telemetry to identify root causes. • Develop and validate targeted fixes — rule tuning, threshold adjustments, feature engineering — and communicate findings clearly to teams. • Analyze trends across case history to identify recurring FP/FN patterns and systemic gaps in detection coverage. • Author well-scoped, well-documented research tickets for novel or unresolved issues, providing sufficient context to accelerate resolution by the expert-DS team. • Serve as the technical bridge between PS/SOCC operations and the core data science research group — translating operational case data into actionable research signals.