Senior Data Scientist & Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Data Scientist & Engineer in India.

This role sits at the intersection of data science, data engineering, and product analytics, offering the opportunity to directly shape how an AI-powered global employment platform evolves. You will work on real product and user data to uncover insights, build scalable data infrastructure, and develop models that directly influence product decisions. Rather than producing static dashboards, your work will drive what gets built next by translating complex data into clear, actionable product direction. In a fast-paced, AI-driven environment, you will own pipelines, experiments, and modeling efforts while collaborating closely with product and engineering teams. The role is ideal for someone who combines strong technical depth with sharp product intuition and enjoys turning data into meaningful business impact.

In this role, you will design and own end-to-end data systems while delivering insights and models that shape product strategy and business decisions. You will work across data engineering, analytics, and machine learning to ensure data is reliable, actionable, and deeply embedded in product development.

• Build and maintain scalable data infrastructure, including pipelines, ETL/ELT processes, and data quality systems.
• Analyze product usage and user behavior to identify key patterns, segments, and actionable insights.
• Develop and deploy machine learning and LLM-based models, including NLP, classification, clustering, and evaluation frameworks.
• Define, track, and refine core product and business metrics such as activation, retention, engagement, and PQLs.
• Design and run experiments including A/B tests, cohort analyses, and causal impact studies.
• Translate data insights into clear product recommendations that influence roadmap and decision-making.
• Collaborate with product, engineering, and GTM teams to embed data-driven thinking across the organization.

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Requirements

The ideal candidate is a versatile data professional with strong experience across data science, engineering, and analytics, combined with a strong product mindset and the ability to influence decisions through data storytelling.

• 5+ years of experience spanning data science, data engineering, and analytics.
• Strong proficiency in SQL and Python for data modeling, analysis, and pipeline development.
• Experience with modern data platforms such as Databricks, Snowflake, or BigQuery.
• Hands-on experience with LLMs, including prompting, embeddings, RAG, fine-tuning, and evaluation.
• Strong grounding in traditional ML techniques such as classification, regression, clustering, and NLP.
• Experience building and maintaining scalable data pipelines in production environments.
• Strong product mindset with the ability to translate data into actionable product decisions.
• Excellent communication skills, with the ability to explain insights to both technical and non-technical stakeholders.
• Experience in early-stage startups or building product analytics from scratch is a strong plus.
• Familiarity with tools such as dbt, Airflow/Dagster, or Spark is preferred.

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Benefits

• Competitive compensation based on experience, skills, and location
• Performance-based bonus eligibility (non-sales roles)
• Flexible work arrangements and remote-friendly culture
• Comprehensive medical, dental, and vision insurance coverage
• Generous paid time off and flexible time-off policy
• Paid parental leave and family support benefits
• Learning and development opportunities with career growth support
• Access to advanced AI and data technologies in a cutting-edge product environment
• Sabbatical eligibility after long-term tenure
• Inclusive, global, and innovation-driven work culture