Staff Data Scientist, Machine Learning

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Data Scientist, Machine Learning based in India.

This is a high-impact, hands-on machine learning role focused on turning complex data into actionable business intelligence.
You will architect and deliver ML, LLM, and AI-agent solutions that automate sophisticated analytics workflows and improve decision-making.
The role spans classical machine learning, real-time anomaly detection, predictive modeling, generative AI, and MLOps.
You will own initiatives from opportunity discovery and prototyping through evaluation, production deployment, and impact measurement.
Working in a fast-paced, data-driven environment, you will partner with senior stakeholders and cross-functional teams to solve ambiguous problems.
You will also establish practical standards for model quality, observability, security, evaluation, and AI cost management.
Beyond individual delivery, you will mentor others and create reusable capabilities that raise the organization’s overall data science maturity.

• Lead the end-to-end roadmap for ML and AI initiatives, from opportunity sizing and experimentation through evaluation, deployment, and measurement of business impact.
• Design and implement real-time anomaly detection models and scalable data-processing systems that identify product usage, adoption, and behavioral signals.
• Apply predictive and prescriptive modeling to business challenges such as churn, revenue forecasting, price sensitivity, marketing mix optimization, segmentation, funnel optimization, and acquisition quality.
• Develop AI agents and automated analytical workflows using LLMs, RAG, embeddings, semantic layers, and agent orchestration frameworks.
• Analyze identity and security-related signals, including unusual login patterns, MFA behavior, authentication velocity, and deviations from historical user activity.
• Build robust ML pipelines supporting both real-time and asynchronous inference, with strong validation, monitoring, and production reliability.
• Establish pragmatic standards and governance for model development, LLM evaluation, observability, security, performance, and AI service cost management.
• Translate complex technical findings into clear business recommendations, communicating trade-offs and insights effectively to senior stakeholders.
• Collaborate across functions to align stakeholders with competing priorities, create clarity in ambiguous environments, and influence strategic outcomes.
• Mentor analysts and other data professionals while developing reusable tools, frameworks, and practices that improve predictive problem-solving across the organization.
• Continuously investigate unfamiliar business domains to identify meaningful signals, features, and appropriate modeling approaches.

Requirements

• 8+ years of professional experience spanning data science, analytics, applied machine learning, and/or LLM-based solutions, with a strong record of delivering business-facing outcomes.
• Advanced expertise in Python, SQL, statistical analysis, and commonly used machine learning frameworks.
• Strong experience with MLOps, including feature engineering, model deployment, inference, monitoring, and production ML pipelines.
• Hands-on experience with LLM APIs, RAG, embeddings, semantic layers, and AI-agent or orchestration frameworks.
• Demonstrated ability to develop real-time anomaly detection models and large-scale data-processing solutions.
• Experience applying predictive and prescriptive analytics to commercial problems such as churn, forecasting, pricing, marketing effectiveness, and customer acquisition.
• Understanding of identity-related threat signals and methods for detecting deviations from historical user behavior is highly valuable.
• Proven ability to design and build AI-powered analytical systems while balancing relevance, performance, reliability, and service costs.
• Strong understanding of segmentation, root cause analysis, funnel optimization, and acquisition quality scoring.
• Experience working in fast-moving, data-first organizations or startup environments where machine learning directly influences business outcomes.
• Excellent business acumen, analytical reasoning, and communication skills, with the ability to explain complex concepts and recommendations clearly.
• Comfortable working independently in ambiguous environments, taking problems from initial exploration through implementation and measurable outcomes.
• Demonstrated curiosity and strategic thinking, with the ability to move between detailed technical analysis and broader business strategy.
• Experience with modern data engineering practices, including data governance, transformation, and orchestration, is preferred.
• Familiarity with recurring-revenue B2B SaaS business models is preferred.
• Strong English communication skills, both written and verbal, are required.
• Candidates must be located in India and authorized to work in India.

Benefits

• Fully remote position within India.
• Remote-first working environment designed to support distributed teams across multiple countries.
• Opportunity to work on challenging ML, LLM, AI-agent, and data analytics problems with meaningful business impact.
• Collaboration with experienced, multidisciplinary teams in a fast-paced SaaS environment.
• Opportunities to influence technical direction, build reusable AI capabilities, and contribute to strategic initiatives.
• Strong opportunities for professional growth, knowledge sharing, mentorship, and technical leadership.
• Inclusive and collaborative culture that values diverse perspectives, innovation, and individual contributions.
• Opportunity to work closely with senior leadership and influence product and business decisions.
• The source description does not specify a salary range or detailed benefits package.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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