Job description
Why We Stand Out Seeking a new challenge where your professional and personal aspirations are not only possible but supported?
Kaufman Rossin might be just the place for you!
Kaufman Rossin Professional Services Private Limited’s (the “Company”) offices are located in the World Trade Center (WTC) in Bangalore, Karnataka, India, and at Udyog Vihar, in Gurgaon, Haryana, India.
The Bangalore office provides a range of services, including risk management, corporate governance, tax, assurance, and family office services.
Out of the Gurgaon office, we render highly specialized back-office alternative investment services for global hedge funds and related fund types.
As one of the top accounting firms in the US, our foundation is “people first”.
In the words of James Kaufman, one of our founders, “We prioritize our people, their development, and their well-being.
Our values are translated into action every day.
" Kaufman Rossin, headquartered in Miami, Florida has been celebrated as the Best Place to Work in South Florida more than a dozen time.
The firm has grown to over 700 employees, with offices spanning the tri-county area and, sister entities, Kaufman Rossin Wealth and Kaufman Rossin Alternative Investment Services.
The Firm is ranked 49th among the top 100 firms in the US by Inside Public Accounting 2023.
Internationally, the Firm has offices in Bangalore and Haryana in India and the Ivory Coast in Africa.
Think you have what it takes?
We're seeking a Senior Data Scientist to lead our predictive analytics initiatives in a CPA and advisory firm.
This role will focus on leveraging advanced analytics and machine learning to drive business impact across client analytics, revenue optimization, and strategic forecasting initiatives.
You'll collaborate with our Business Intelligence team and business leaders to deliver impactful data science solutions.
This is a high-impact individual contributor role in a growing analytics function How You’ll Contribute: Predictive Modeling & Machine Learning Build, validate, and deploy cross-sell prediction models using client engagement data, service utilization patterns, and industry benchmarks Develop time-series forecasting models for expense projection, cashflow forecasting, and revenue prediction across service lines Implement model monitoring, retraining pipelines, and performance tracking to ensure accuracy over time Apply advanced machine learning techniques to improve model performance and business outcomes LLM & Generative AI Integration Explore and implement LLM applications for client data analysis, proposal generation insights, and automated reporting Evaluate opportunities for RAG (Retrieval Augmented Generation) systems using firm knowledge bases Stay current on AI/ML advancements and recommend practical applications for professional services Client Segmentation & Analytics Design clustering and segmentation models to identify client growth potential and engagement patterns Analyze historical engagement data to uncover patterns driving successful client relationships and revenue expansion Collaboration & Communication Partner with Business Intelligence team to translate models into actionable business recommendations and insights Present findings to firm leadership in clear, business-oriented terms Document methodologies and create reproducible workflows for model handoffs Technical Leadership Establish best practices for model development, validation, and deployment Evaluate and recommend ML tools, platforms, and approaches as our analytics capabilities grow Work-Life Balance People First Company Hybrid work policy Working directly with peers in the US We embrace authenticity.
Kaufman Rossin is an equal-opportunity employer.
We are committed to creating a culture that reflects the diversity of our firm and clients.
We encourage understanding, acceptance, and celebration among all people.
That includes lifestyle, education, experience, race, ethnicity, age, religion, physical ability, sexual orientation, and gender identity.
Differences make unique varieties.
What Skills You’ll Bring: Experience 5-8 years of professional experience in data science, with at least 3 years building production ML models Proven track record of deploying forecasting models (time-series, regression) that drove business decisions Experience with customer segmentation, propensity modeling, or similar predictive analytics Demonstrated ability to work autonomously with minimal technical oversight Technical Skills Expert-level proficiency in Python or R for ML/statistical modeling (scikit-learn, XGBoost, Prophet, statsmodels, etc.
) Strong SQL skills for data extraction and feature engineering Experience with model validation techniques (cross-validation, A/B testing, backtesting) Familiarity with MLOps practices : version control (Git), experiment tracking, model monitoring Familiarity with LLMs and Generative AI and eagerness to implement GenAI solutions - exposure to OpenAI API, LangChain, or similar frameworks preferred Business Acumen Experience in professional services, B2B SaaS, or similar client-centric industries preferred Ability to translate business problems into ML frameworks and vice versa Strong communication skills - can explain complex models to non-technical stakeholders How You'll Stand Out Experience with BI platforms (Domo, Tableau, Power BI) Knowledge of CRM systems and APIs (Salesforce, HubSpot) Cloud platform experience (AWS SageMaker, Azure ML, GCP Vertex AI) Familiarity with accounting/finance metrics and professional services business mode
This job post has been translated by AI and may contain minor differences or errors.
