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Mid-level ML role at a well-known services firm, metro location and broad skills increase competition.
Strong Finance & Accounting domain focus reduces cross-industry transferability of candidates.
Requires F&A domain expertise plus ML, Python, deployment and data engineering collaboration, creating moderate rigor.
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Develop and deploy advanced analytics and predictive models in Finance & Accounting to support decision-making in financial forecasting, cost optimization, working capital analysis, and risk assessment.
Collaborate with Finance and FP&A stakeholders to identify opportunities, translate business needs into technical requirements, and deliver actionable insights through automated tools and dashboards.
Ensure data quality by partnering with Data Engineering, maintain model explainability aligned with finance metrics, and stay updated on finance analytics trends.
Work Experience Required: Not explicitly mentioned in the JD.
Bachelor’s degree in Business Analytics, Computer Science, Statistics, or relevant Master’s in Data Science.
Proficiency in Python, SQL, and statistical/machine learning/AI modeling with understanding of underlying assumptions.
Experience with finance domain analytics, developing BRD & TRD, and building data science solutions supporting Finance stakeholders.
Experienced in bridging data science and finance, particularly skilled at applying analytics to Finance & Accounting challenges.
Capable of independently handling end-to-end analytics projects including data wrangling, model development, deployment, and stakeholder communication.
Comfortable working in innovation-driven, fast-paced environments leveraging advanced analytics, with ability to translate complex business needs into technical solutions.