Introduction About SymphonyAI SymphonyAI is a leading global enterprise AI SaaS company transforming industries through proven, predictive and generative AI solutions. We partner with leading global organizations, consultancies and global system integrators (GSIs) to accelerate innovation and go-to-market velocity at scale. Serving Fortune 500 companies across Retail/CPG, Financial Services, Manufacturing, Media, and IT/Enterprise Service Management, we deliver measurable business outcomes through cutting-edge technology and deep domain expertise. Join our global team of innovators and help shape the future of AI-powered enterprise solutions in a collaborative, high-growth environment where your work creates real-world impact. Job Description The Opportunity: This Data Scientist role offers the chance to make meaningful research and development contributions within a cutting‑edge machine learning environment. You’ll work closely with AI Researchers and Data Scientists to advance the core Sensa platform by building, evaluating, and deploying sophisticated machine learning models. A big part of the position involves staying current with the latest scientific literature, helping shape future R&D initiatives, and co‑authoring research-oriented white papers. Day‑to‑day, you’ll work with extremely large datasets, contribute to production‑level code, and support ML/Data Engineers with model deployment and pipeline configuration. The position is well‑suited for someone with a strong mathematical and statistical foundation in machine learning, high proficiency in Python and its data ecosystem, and the ability to operate both independently and collaboratively in a fast‑paced startup setting. Candidates with experience in Kubernetes, Kubeflow, Dask, Rapids, blockchain technologies, DeFi, or financial crime analytics (AML, fraud, trade surveillance) will stand out, though these skills are considered bonuses rather than requirements. Responsibilities: - Make research and development contributions to our core product offerings. - Collaborate on research machine learning white papers. - Continuously review the latest scientific papers and contribute ideas for future R&D projects. - Build, evaluate and deploy machine learning models using the Sensa platform. - Collaborate with AI Researchers in R&D - Collaborate with other Data Scientists on Sensa deployment projects. - Support ML and Data Engineers with models and pipeline deployment and configurations. - Perform data analysis on extremely large tabular data. Key Requirements: - Bachelor’s degree in computer science, information technology, engineering, mathematics, statistics, or physics. - Deep knowledge of the statistical and mathematical basis of machine learning algorithms. - High proficiency in Python, Pandas, NumPy, and scikit-learn. - Ability to contribute to production codebase. - The capability to work independently in a fast-paced start-up environment. - The ability to collaborate well with other data scientists and machine learning engineers. - Willingness to learn new technologies on the job. - Experience using Github. Bonus Requirements: - Knowledge of Kubernetes, Kubeflow, Dask, and Rapids. - Knowledge of Blockchain, DeFi, and DAGs. - Knowledge of Anti Money Laundering, Financial Fraud, and Trade Surveillance. #LI-Remote About Us Who We Are SymphonyAI is building the leading enterprise AI SaaS company for digital transformation across the most critical and resilient growth industries, including retail, consumer packaged goods, financial crime prevention, manufacturing, media, and IT service management. Since its founding in 2017, SymphonyAI today serves 1600+ Enterprise customers globally and has grown to 2,300 talented leaders, data scientists, and other professionals across over 30 countries.

• Build, maintain, and improve decision systems and predictive models that are key to Progressive Leasing’s competitive advantage • Explore new data sources both internal and external to Progressive and use findings to further improve model performance • Design, implement, and read in-market experiments testing new algorithms, technologies, and processes • Prototype solutions to business problems using cutting-edge technologies • Recommend and support strategic changes through rigorous analytics, creative problem solving • Identify, evaluate, and help implement advanced analytics methods • Be part of a collegial team of like-minded data scientists!

• Build analytic solutions and machine learning models (e.g. classification, ranking) to optimize Utilization Management in healthcare and translate business logic or healthcare workflow into data-driven decisions • Develop data structures and processing pipelines to organize, collect, and standardize insights from both unstructured data (PDFs, texts, images) and structured data, to address both reporting needs and feature development • Explore and build LLM-powered pipelines and evaluate performance based on real-world feedback • Create and evaluates the data needs of assigned projects and assures the integrity of the data • Explore existing data and recommends additional sources of data for improvements • Document projects including business objectives, data gathering and processing, detailed set of results and analytical metrics

(Fully-remote US position) About LiftLab Liftlab is the leading provider of science-driven software to optimize marketing spend and predict revenue for optimal spend levels. We call this the Science of Marketing Effectiveness. Our platform combines economic modeling with specialized media experimentation so brands and agencies can clearly see the tradeoffs of growth and profitability. With decades of experience in marketing analytics and data science, our team of industry experts and thought leaders is proud to enable leading and emerging brands such as Cinemark, Express, Hanna Anderson, Lulu & Georgia, Pandora, Sephora, Skims, Tory Burch, Thrive, and Vionic, with our cutting-edge solutions and strategic guidance. Job responsibilities - Develop new algorithm-based features of LiftLab’s marketing measurement and optimization platform - Performs diagnostics and root-cause analysis and provide fixes - Works with Data Science and Engineering to implement these features into LiftLabs product and workflow Course work/experience: - Data manipulation - SQL - Operating on big datasets in Python - Data visualization - Mathematical optimization - Linear optimization concepts - Nonlinear continuous optimization - Linear algebra - Mathematical modeling - Using parametrized systems of equations to represent real-world systems - Statistics - Multivariate regression - Clear understanding of Maximum Likelihood estimation and computational methods to find MLE parameters - Bayesian concepts - Hypotheses testing Education requirements Graduate degree in Applied Mathematics, Scientific Computing, Operations Research or related field. We will consider holders of Bachelor degrees with relevant experience Skills/Aptitude - Engineering and detective mindset - Both to diagnose data and existing algorithms and to develop new analytics functionality - Pragmatic approach to real-world problems - Focus on problem solving over applying specific models - Willingness to make approximations and assumptions rather than find “the” optimal solution - Ability to combine multiple techniques and models to solve end-to end-problems - Communication and collaboration skill - Ability to convert non-technical requests into project specifications