• Lead the design, development, and deployment of advanced machine learning, forecasting, optimization, and generative AI solutions that power financial planning, analysis, and decision-making. • Partner closely with Finance leadership and other key business stakeholders to translate financial questions into rigorous data science problems. • Build machine learning systems from the ground up and design scalable data science infrastructure that Finance teams can rely on. • Strategically determine the most appropriate modeling approach (traditional ML, forecasting, optimization, or Generative AI) for each problem, and design experiments to evaluate competing approaches. • Deliver cutting-edge forecasting, anomaly detection, and optimization expertise, driving best practices across financial modeling at ServiceTitan. • Transform model outputs into actionable, executive-ready business recommendations. • Champion and execute long-term strategic projects that improve how ServiceTitan plans and operates financially. • Collaborate closely with engineering and product teams to seamlessly deploy models into production, ensuring scalability and performance. • Mentor data scientists on the team and elevate the technical bar across forecasting, optimization, and GenAI work. • Invent bold and creative solutions to current and future business problems.

• Communicate with stakeholders to determine institutional goals, and design analyses and data visualizations to provide insight to complex business problems. • Conduct exploratory data analysis in collaboration with subject matter experts to build and validate analytical datasets. • Develop statistical and machine learning models (classification, time series, etc.) using a custom python framework to generate scores and forecasts. • Present predictive modeling results and operational dashboards to end-users at colleges and universities to help them understand and make use of the findings and scores. • Work with data science and data engineering teams to build data pipelines, improve internal systems, and deploy and maintain models in a production environment. • Collaborate with other data scientists to share knowledge, develop best practices, and contribute to documentation, process standardization, and product development. • Occasionally travel (typically 1-3 days at a time, ~3 times per year) to HelioCampus offices and client sites for meetings and presentations.

Role Description We're looking for a Product Data Scientist excited to help build the bank of the future. You'll have the opportunity to supercharge our user engagement in 2025 and help us to build a bank that customers truly love. At Monzo, we're building a bank that is fair, transparent, and a delight to use. We’re growing extremely fast and have over four and a half million customers in the UK, with over 100,000 new people joining every month. We’ve built a product that people love, and more than 80% of our growth comes from word of mouth and referrals. We work in cross-functional squads where every data scientist is a member of a central data discipline and fully embedded into one product squad alongside engineers, designers, marketers, product managers, etc. - Applying your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with our products and how those insights can inform our product strategy. - Guide and enable product teams to measure things that matter; initiate or help run A/B experiments to keep improving everything we do. - Drive together with the finance team a unified company-wide understanding of the lifetime value of our users and how different product features are impacting user profitability. - Liaise with engineers to keep making sure we collect the right data to produce relevant business insights. Qualifications - Impact driven and eager to have a real positive impact on the company, product, users, and colleagues. - Commercially minded and can put numbers into business perspective. - Comfortable getting hands-on as well as thinking strategically. - Self-starter mindset; proactively identify issues and opportunities. - Team player whom colleagues can rely on. - Solid grounding in SQL and preferably Python. - Experience in conducting large scale A/B experiments. Requirements - Our average interview process takes around 2-3 weeks. - Opportunity to speak to our recruitment team at various points during the process. - Contact for specific questions or reasonable adjustments: tech-hiring@monzo.com. Benefits - £55,000 to £75,000 + Incentive Awards tied to your performance + Benefits. - Relocation assistance to the UK. - Visa sponsorship available. - Flexible working hours with trust to work enough hours to do your job well. - Learning budget of £1,000 a year for books, training courses, and conferences. - Part-time work options available. Company Description Diversity and inclusion are a priority for us, and we’re making sure we have lots of support for all of our people to grow at Monzo. At Monzo, we’re embracing diversity by fostering an inclusive environment for all people to do the best work of their lives with us. This is integral to our mission of making money work for everyone. We’re an equal opportunity employer. All applicants will be considered for employment without attention to age, ethnicity, religion, sex, sexual orientation, gender identity, family or parental status, national origin, or veteran, neurodiversity or disability status.

Title: Data Scientist - Marketing Location: Lititz United States Job Description: Job Summary Webstaurant Store, the world's largest online restaurant supply company, is looking for a full-time Data Scientist to join the Data Science team. The Data Scientists are responsible for supplying statistical rigor to the organization's analytics projects, aimed at discovering actionable insights and opportunities for growth and optimization. This role can be remote in some US states (See below for remote work requirements) or based in one of our offices (Lititz, PA or Tampa, FL). Remote Work Qualifications - Access to a reliable and secure high-speed internet connection. Cable or fiber internet connections (at least 75mbps download/10mbps upload) are preferred, as satellite connections often cannot support the technologies used to perform day-to-day tasks. - Access to a home router and modem. - A dedicated home office space that is noise- and distraction-free. The space should have strong wireless connection or a wired Ethernet connection (wired connection is preferred, if possible). - A valid, physical address (apartment, suite, etc.). PO Boxes are not supported, as a physical address is required for you to receive your computer equipment. - The desire and ability to work and communicate with other team members via chat, webcam, etc. - Legal residents of one of the following states: (AK, AL, AR, AZ, CT, DE, FL, GA, IA, ID, IN, KS, KY, LA, MD, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NM, NV, OH, OK, PA, SC, SD, TN, TX, UT, VA, VT, WI, WV, and WY). We only accept W-2 candidates, H-1B sponsorship is not available. Responsibilities Responsibilities include, but are not limited to: - Advising on analysis and modeling techniques, selecting the best fit for structured & unstructured, complex data, and developing custom analytics models to generate insights that drive value for our customers and unlock competitive advantage for our organization. - Collaborating with our analytics engineers to gather the right information from various sources so that you can implement advanced statistical methodologies and design interventions to optimize our business performance. - Conducting exploratory analysis including hypothesis testing, statistical inference, and statistical analysis (predictive and/or prescriptive). - Maintaining and updating our in-house Media Mix Models (MMM) and Multi-Touch Attribution (MTA) models to ensure they reflect the current state of marketing spend and value - Designing, implementing, and analyzing lift / blackout / other experiments to continually improve our attribution models - Partnering with business and technical stakeholders, including our Google account team, to translate complex retail challenges into data science solutions. - Developing processes and tools that monitor, analyze and continuously improve model performance and data accuracy. - Work with other data scientists to design and implement experiments and glean actionable insights from experimental analyses. - Defend and explain the validity of predictive/ML models to those without a background in data science or statistics. - Actively research new tools and technologies, staying on top of analytics news and best practices. Physical Requirements - Work is performed while sitting/standing and interfacing with a personal computer. - Requires the ability to communicate effectively using speech, vision, and hearing. - Requires the regular use of hands for simple grasping and fine manipulations. - Requires occasional bending, squatting, crawling, climbing, and reaching. - Requires the ability to occasionally lift, carry, push, or pull medium weights, up to 50lbs. Qualifications Experience - Minimum 2 years of professional experience in Data Science, or a PhD in mathematics, statistics, economics, or a related quantitative field. - Advanced proficiency in Python and SQL, with strong foundation in statistical methods and advanced modeling techniques applied to marketing and growth problems. - Hands-on experience with experimentation and causal inference frameworks, including incrementality testing, geo experiments, holdout designs, or quasi-experimental methods. - Proven ability to partner with paid marketing teams to design, execute, and analyze experiments that inform budget allocation and channel strategy. - Experience building, evaluating, or refining Media Mix Models (MMM) and/or Multi-Touch Attribution (MTA) models to quantify marketing impact and reduce uncertainty. - Ability to translate complex model outputs into clear, credible insights that drive stakeholder buy-in and influence marketing decision-making, even without direct ownership of spend. - Comfortable navigating trade-offs between model rigor, business timelines, and practical adoption by paid media stakeholders. Education This role does not require a degree. We value relevant skills and experience and alignment with our core values above all else. Desired Traits & Skills The ideal candidate will possess the following qualities: - You Communicate Effectively: Ability to explain ideas simply and confidently to team members both written and verbally. - You have an Entrepreneurial Spirit: Takes it upon themselves to find ways to add value to the team and business. They are self-motivated and creative in their quest to find actionable insights and new solutions. They can often be found saying "What if we tried this?" or "Maybe this is a better way to do it?" They have a knack for overcoming obstacles. - You Desire to Grow: Constantly seek to improve themselves and expand their professional knowledge and skill set. - You're an inquisitive, out-of-the box thinker who's continually on the lookout for opportunities to improve and innovate data science solutions. - You have consistently high standards; your passion for quality is inherent in everything that you do. - Familiarity with a variety of supervised/unsupervised/reinforcement learning methods. - Demonstrable portfolio (git repos, kaggle competitions, etc) of machine learning projects. - You have proven ability as a full stack data scientist who develops, experiments, optimizes, and scales models for the production environment. - You connect the how and why, using your knowledge of data science theories and methodologies to derive the best approach that is fit-for-purpose.