Role Description Our client is a trailblazer in membership management, offering tailored solutions to the unique challenges faced by modern Trade Unions. They are currently looking for a passionate Business Intelligence Engineer / Data Scientist to join their dynamic team. You'll be responsible for deep diving into company and client data, cleaning and analysing datasets, and extracting meaningful insights that drive business decisions. Your role will involve: - Deep diving into company and client data to clean, analyse, and extract meaningful insights that drive business decisions. - Developing and maintaining BI dashboards, primarily using Power BI. - Designing predictive models and AI-driven solutions to support business objectives. - Translating business requirements into actionable, data-driven outcomes. - Mentoring junior analysts, helping them navigate complex data challenges. - Automating recurring processes and troubleshooting data-related issues. - Collaborating with Senior BI Analysts and the Head of BI to contribute to the broader BI strategy. Qualifications - 5+ years in a Business Intelligence Engineer, Data Scientist, or similar role. - Relevant Degree. Requirements - Must-Have Technical Skills: - Power BI: Proficiency in developing and maintaining dashboards. - Python: Strong programming skills, including experience with data science packages such as NumPy, Pandas, Scikit-learn, and TensorFlow. - Data Visualization: Expert ability to create clear and impactful visual representations of data. - Additional Technical Skills: - SQL: Proficiency with MySQL, T-SQL, and Graph databases. - Soft Skills: - Strong ability to translate business needs into technical solutions. - Proven capability to work autonomously while thriving in a collaborative team environment. - Experience mentoring junior team members. Benefits - Passionate: Demonstrates a genuine enthusiasm for data analysis, AI, and deriving insights. - Ownership: Takes autonomy over projects and is committed to delivering accurate, high-quality work. - Growth-Oriented: Actively seeks continuous learning and mastery opportunities, particularly in AI and advanced analytics. - Collaborative: Works effectively with stakeholders across the organization and within a dynamic team. - Detail-Oriented: Maintains a focus on data accuracy and consistency while meeting tight deadlines.

Company Cox Automotive - USA Job Family Group Data Intelligence & Science Job Profile Sr Data Scientist Management Level Individual Contributor Flexible Work Option Can work remotely anywhere in the specified country Travel % No Work Shift Day Compensation Compensation includes a base salary in the range of $101,500.00 - $169,100.00. The base salary may vary within the anticipated base pay range based on factors such as the ultimate location of the position and the selected candidate’s knowledge, skills, and abilities. Position may be eligible for additional compensation that may include an incentive program. Job Description The Insights & Advisory team at Cox Automotive is seeking a highly skilled Senior Data Scientist to lead the development of advanced analytics and AI/ML models that power innovative products and inform strategic decisions. This role blends deep expertise in statistical modeling, econometrics, machine learning, and AI acceleration with strong business acumen to deliver actionable insights for internal teams and automotive OEM clients. As a Senior Data Scientist, you will work end-to-end on analytics projects – from data preparation and model development to deployment, governance, and stakeholder communication – with emphasis on market share modeling and reporting, macroeconomic forecasting, financial modeling and engineering, and strategic analytics. You’ll work independently across all phases of analytics projects, from data preparation and model development to deployment and stakeholder communication, while championing responsible AI practices and mentoring junior team members. Key Responsibilities: Advanced Analytics & AI/ML Development - Design, develop, and implement predictive, prescriptive, and optimization models using advanced statistical and machine learning techniques. - Utilize AI tools for rapid ML prototyping, automated feature engineering, and hyperparameter optimization. - Integrate AI-enhanced models into production systems and establish automated monitoring frameworks. - Apply interpretability frameworks (e.g., SHAP, LIME) and AI-driven insights to communicate results effectively. Data Analysis & Modeling - Translate business problems into analytical solutions and select appropriate methodologies. - Perform data preparation, feature engineering, and validation for large, complex datasets. - Deliver production-ready code and collaborate with engineering teams for deployment. Market, Economic, and Business Modeling - Develop and maintain methodologies for estimating and reporting market share while also building models that leverage demographic, inventory, demand, pricing, and other relevant data sources. - Create macroeconomic and business forecasting models to anticipate trends and inform strategic decisions. - Design financial models and apply advanced techniques to evaluate incentives, pricing strategies, and profitability, while remaining adaptable to emerging business needs and diverse datasets. Strategy and Internal Consulting - Serve as an internal consultant, framing business problems and aligning solutions with strategic objectives. - Facilitate decision-making using structured approaches; leverage negotiation and conflict resolution skills to drive consensus. Data Engineering & Governance - Own data preparation, feature engineering, validation, and production-ready code in Python and SQL. - Partner with engineering to integrate models, automate monitoring, and ensure reliability. - Establish responsible AI practices including bias detection, interpretability, and compliance monitoring. Collaboration, Leadership & Communication - Partner with product, engineering, and business stakeholders to align models with strategic goals. - Present findings and recommendations clearly to both technical and non-technical audiences. - Mentor junior staff, contribute to team capability building, and engage in thought leadership. Minimum Qualifications: - Bachelor’s degree in Statistics, Econometrics, Operations Research, Applied Mathematics, Computer Science, Economics, or a related quantitative field and 4 years’ experience in a related field. The right candidate could also have a different combination, such as a master’s degree and 2 years’ experience; a Ph.D. and up to 1 year of experience; or 16 years’ experience in a related field - Proven experience applying descriptive, predictive, and prescriptive analytics to real-world business problems. - Strong background in statistics and econometrics, including panel data analysis, time series modeling, and causal inference. - Hands-on experience with market share modeling and reporting. - Experience in macroeconomic forecasting and financial modeling/engineering. - Proficiency in Python and SQL, with ability to deliver production-quality code and manage the full ML lifecycle. - Experience with AWS or other cloud platforms and collaboration with engineering teams for deployment. - Ability to integrate models into enterprise systems and maintain production-ready code. - Experience operating as an internal consultant within a complex enterprise environment. - Exceptional communication and problem-solving skills. Preferred Skills - Advanced statistical techniques: GL GLMs, time series, forecasting, clustering, PCA; causal and panel methods. - Optimization methods: linear/mixed integer programming, heuristic approaches, network flow. - ML frameworks: scikit learn, TensorFlow, PyTorch; model interpretability with SHAP and LIME. - Experience with data visualization tools (Tableau, Power BI) and compelling storytelling. - Knowledge of CI/CD pipelines, data governance, and Agile methodologies. - Market share modeling approaches: discrete choice, multinomial and nested logit, demand elasticity. - Financial engineering: risk models, Monte Carlo, scenario analysis, option style incentive evaluation. - AI accelerated development and agentic frameworks; CI/CD and Agile delivery. - Data visualization and storytelling with Tableau or Power BI. - Evidence of peer reviewed publications or conference presentations. Why Join Cox Automotive? At Cox Automotive, data science drives innovation. As a Sr Data Scientist, you’ll shape the future of AI-powered analytics, deliver impactful insights, and mentor the next generation of data talent, all while working in a collaborative, forward-thinking environment. Drug Testing To be employed in this role, you’ll need to clear a pre-employment drug test. Cox Automotive does not currently administer a pre-employment drug test for marijuana for this position. However, we are a drug-free workplace, so the possession, use or being under the influence of drugs illegal under federal or state law during work hours, on company property and/or in company vehicles is prohibited. Benefits The Company offers eligible employees the flexibility to take as much vacation with pay as they deem consistent with their duties, the company’s needs, and its obligations; seven paid holidays throughout the calendar year; and up to 160 hours of paid wellness annually for their own wellness or that of family members. Employees are also eligible for additional paid time off in the form of bereavement leave, time off to vote, jury duty leave, volunteer time off, military leave, and parental leave. About Us Through groundbreaking technology and a commitment to stellar experiences for drivers and dealers alike, Cox Automotive employees are transforming the way the world buys, owns, sells – or simply uses – cars. Cox Automotive employees get to work on iconic consumer brands like Autotrader and Kelley Blue Book and industry-leading dealer-facing companies like vAuto and Manheim, all while enjoying the people-centered atmosphere that is central to our life at Cox. Benefits of working at Cox may include health care insurance (medical, dental, vision), retirement planning (401(k)), and paid days off (sick leave, parental leave, flexible vacation/wellness days, and/or PTO). For more details on what benefits you may be offered, visit our benefits page. Cox is an Equal Employment Opportunity employer – All qualified applicants/employees will receive consideration for employment without regard to that individual’s age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, physical or mental disability, veteran status, genetic information, ethnicity, citizenship, or any other characteristic protected by law. Cox provides reasonable accommodations when requested by a qualified applicant or employee with disability, unless such accommodations would cause an undue hardship. Application Deadline: 03/30/2026

• You will lead SAC's data science and analytical work -- building and improving estimation and forecasting models, ensuring data quality and methodological rigor, and translating complex datasets into actionable insights for partners, shelters, and the public. • You'll also collaborate on data reporting, data visualization/dashboarding and peer-reviewed research, and represent SAC's data expertise both internally and at national conferences. • This role involves hands-on work with Shelter Animals Count's database (for example, frequent analysis of datasets including 20M+ animals, many parameters).

• Support program initiatives from inception to deployment, ensuring alignment with CBM+ business and mission objectives. • Lead development and deployment of machine learning models, statistical analyses, and data experiments. • Own the analytical framework, ensuring robustness, reproducibility, and scalability. • Partner with domain experts to translate business questions into data-driven insights and products. • Promote and refine standards for experimental design and analysis. • Oversee data collection & processing, including implementation/sustainment of ETL pipelines, as well as cleaning and preprocess datasets for usage. • Perform EDA, to include, performing statistical analysis and visualization to understand data patterns, identifying correlations, trends, and insights to drive product development. • Lead ML model development using regression, classification, clustering, & deep learning while optimizing models for accuracy, performance, and scalability. • Collaborate with a multi-functional team to integrate models into applications or APIs. • Continuously monitor deployed models for performance drift and degradation.