Lead and perform analytical projects to support key marketing and sales strategic objectives for the US Commercial Excellence team.
Responsibilities
Lead projects in Business Performance Analytics, Sales Force Optimization, ROI/Impact Analysis, Forecasting, Digital Marketing Analytics, and Market Research
Develop and adopt advanced analytical approaches/methodologies
Hands‑on analytics utilizing statistical data modeling and advanced analytics techniques using tools like SAS, R, Python, Power BI, Alteryx
Partner with Sales Operations and Data Strategy teams to evolve CRM and data warehouse
Collaborate with stakeholders to identify KPIs and deliver actionable insights through BI reporting tools
Requirements
Bachelor's degree or above
Preferred: Degree in Analytics, Mathematics, Statistics, Computer Science, Engineering, Economics, or another quantitative discipline
Lead independent investment research, develop analytical frameworks, and partner with data science and engineering teams to support capital deployment decisions.
Responsibilities
Own self‑managed research roadmap
Conduct independent deep‑dive research sprints
Define requirements for dynamic analytics tools
Build MVPs and prototypes using AI‑assisted tools
Analyze housing market trends and macroeconomic factors
Requirements
Bachelor's or master's degree in Data Science, Statistics, Economics, Finance, Applied Mathematics, Computer Science, Engineering, or a related quantitative field
Nice to have: Master's degree or PhD in Data Science, Statistics, Economics, Finance, Operations Research, or MBA with a quantitative focus
Nice to have: Experience within real estate, private equity, investment management, asset management, or financial services
Nice to have: Experience developing predictive pricing, forecasting, or optimization analyses
Nice to have: Experience utilizing geospatial analytics and external market data sources
Support Target's leadership team with critical data analysis to drive profitable decisions and scalable decision-making in the modern retail market.
Responsibilities
Translate business problems into well-defined analytical questions and structured approaches
Support scenario, decision, and action modelling to evaluate business trade-offs and inform recommended actions
Partner with Target business stakeholders to understand priorities and roadmaps, validate analytical requirements, and present insights and recommendations with clarity and impact
Develop and deliver analytical and AI-driven solutions (including GenAI, Agent, and Agentic approaches) that enable decision support, forecasting, optimization, and automation
Apply advanced analytics techniques, including causal, predictive, and prescriptive analytics, to drive deeper understanding of business levers and inform optimal actions
Requirements
B.Tech / B.E.
Masters in Statistics/Econometrics/Mathematics equivalent
BA/BS in a quantitative degree – Math, Statistics, Econometrics, Data Sciences, Computer Science
The Senior Power BI & Data Analyst transforms complex commercial, operational and financial data into actionable insights that support strategic decisions, revenue growth, profitability and operational efficiency.
Responsibilities
Design and maintain enterprise Power BI dashboards, reports and semantic models.
Build advanced DAX measures, Power Query transformations and dimensional models.
Integrate ERP, CRM, finance and supply chain data; implement row-level security and refresh monitoring.
Developing innovative data products and implementing automation, advanced AI/ML, and Generative AI capabilities to drive business value through demand forecasting and analytics.
Responsibilities
Develop and maintain high-accuracy short-term and long-term demand forecasts at Automotive Segmentation and Powertrain levels.
Build, validate, and deploy time-series models (e.g. ARIMA) and ML algorithms to identify market trends.
Proactively integrate Generative AI / Agentic AI and other modern AI tools into daily workflows.
Act as a strategic partner to Sales, Marketing and Finance teams, translating analytical outputs into clear business recommendations.
Lead monthly forecasting reviews, presenting findings to senior stakeholders.