Data Scientist - People Analytics (AutoPH Team)
HighRadius
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Job Description
HighRadius provides a single Agentic AI platform for the Office of the CFO. It integrates 180+ agents that orchestrate end-to-end processes across Order-to-Cash, Close & Reconciliation, Consolidation & Reporting, Accounts Payable, B2B Payments, and Treasury. HighRadius guarantees operational KPI improvements by mapping them to specific agents on the platform. With a 3-6 month go-live period, HighRadius drives value creation at 1300+ enterprises such as 3M, Unilever, Bristol-Myers Squibb Company, Red Bull, Lufthansa, and more. HighRadius has been consistently recognized as a market leader by Gartner, IDC, and Forrester.
Job Summary
We are redefining how performance is measured and rewarded. As a Data Scientist within the AutoPH Strategy Team, you won't just be analyzing data—you will be architecting the algo that drives our next-generation Performance Management System.
Contributing directly to the CEO's strategic vision, you will engineer the correlation between behavioral inputs and business outputs, and build the algorithms that ensure our organization remains a meritocratic, high-growth environment.
Key Responsibilities
- Algorithm Engineering & PMS Innovation
- The AutoPH Engine: Own the statistical logic behind our Autonomous Performance@ HighRadius system. You will design, test, and iterate on algorithms that balance Output (results), Input (effort), and Culture KPIs.
- Model Evolution: You will critically evaluate our AutoPH logic and identify where our measurement systems lack precision. You will engineer the enhancements required to make our performance algorithms mathematically sound and bridge the gap between what we currently track and what we actually aim to measure.
- Predictive talent strategy: Move from reactive reporting to proactive intervention. You'll implement ML frameworks (Time Series, Clustering, LLMs among others) to predict talent density, flight risks, and high-potential trajectories.
- From Concept to Code: Develop Python scripts to transition theoretical HR models into deployable ML APIs that integrate seamlessly with our business stack.
- Statistical Rigor & Correlation Research
- Cracking the Input/Output Code: - You will apply advanced statistical methods (correlation studies, causal inference, multivariate analysis among others) to prove (or disprove) which effort metrics actually move the needle on business outputs.
- Bias Mitigation: Use advanced normalization and cohort analysis to eliminate noise and systemic bias in performance grading, ensuring a level playing field for every employee.
- Data Integrity: Define the taxonomy for performance data. You'll ensure that our data architecture is clean, scalable, and audit-ready.
- Productized Analytics & Storytelling
- Insight Systems: Don't just build reports—build products. Architect scalable, intuitive Power BI/Tableau dashboards that allow leaders to self-serve insights.
- Narrative Building: Translate high-dimensional math into low-friction business narratives for the C-suite. You are the bridge between raw data and strategic execution.
- The Toolkit: Solid foundation in Python and SQL and experience within the modern ML stack (Scikit-learn, TensorFlow/PyTorch) and BI tools (Power BI/Tableau).
- The Experience: 5+ years in Data Science, with at least 2-3 years preferably embedded in People Analytics or Talent Product environments. You understand the nuances of human data.
- The Product Mindset: You've moved past simple data requests. You have experience identifying pain points in a system (like a legacy PMS) and engineering a technical solution to fix them.
- Mathematical Grit: You are comfortable with complex variables, cohort normalization, and the challenge of quantifying the unquantifiable aspects of human performance.
- High Visibility: This isn't a back-office HR role. You are building a core piece of our company's operating system under a CEO-led initiative.
- Complexity: You'll be dealing with one of the hardest data problems: predicting and optimizing human behavior at scale.
- Autonomy: We value scientific objectivity. You are expected to challenge the status quo if the data suggests a better way forward.
About The Company
HighRadius
HighRadius offers AI-driven Autonomous Finance Solutions for the Office of the CFO. More than 800 of the world’s leading companies have transformed their Order to Cash, Treasury, and Record to Report processes with HighRadius. Our customers include 3M, Unilever, Anheuser-Busch InBev, Sanofi, Kellogg Company, Danone, Hershey’s and many more. Autonomous Software is data-driven software that continuously morphs its behavior to the ever-changing underlying domain transactional data. It brings modern digital transformation capabilities like AI, Robotic Process Automation, Natural Language Processing and Connected Workspaces as out-of-the-box features for the finance & accounting domain. Finance business stakeholders have been led to believe that they have only two choices: pick an application software vendor that digitizes a paper or Excel-based process to an electronic system of record, or, choose a middleware platform for AI or RPA to build and maintain in-house, domain-specific capabilities. In contrast, HighRadius Autonomous Software combines the best of both worlds to deliver measurable business outcomes such as DSO reduction, working capital optimization, bad-debt reduction, reduce month close timelines, and improved productivity in under six months.
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