Full-Time

Sr. Staff Data Scientist

Marketing

Posted on 5/27/2025

Databricks

Databricks

10,001+ employees

Data lakehouse platform for analytics

No salary listed

Bengaluru, Karnataka, India

Hybrid

Category
Data & Analytics (4)
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Requirements
  • Degree in a quantitative field (e.g., Data Science, Statistics, Computer Science, Marketing Analytics, or a related discipline)
  • 7+ years of experience in marketing analytics, marketing data science, or business intelligence, ideally in B2B SaaS or marketplace environments
  • Proven experience with B2B marketing funnels, campaign KPIs (e.g., conversion rates, CAC, ROI), and performance measurement
  • Proficiency in Python (or R) with libraries like pandas, NumPy, scikit-learn, or statsmodels for data analysis and modeling
  • Strong grasp of causal inference methods and experience applying them in real-world marketing use cases
  • Experience with experimentation platforms, A/B testing frameworks, and interpreting results at scale
  • Skilled at relationship building, communications, and project management to drive strategic alignment and execution across stakeholders at all levels.
Responsibilities
  • At Databricks our mission to democratize data and AI. We are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world’s best data and AI infrastructure and making it accessible for companies of any size to easily self-serve the platform capabilities to derive data insights and accelerate decision making.
  • In this role, you’ll help scale our marketing impact by building data-driven insights and predictive models that shape messaging, channel strategy, and customer engagement across the funnel. You'll partner closely with Marketing, Product, Sales, and Engineering to deliver measurement frameworks that drive real-time optimization and long-term growth.
  • Outcomes You Will Drive:
  • Attribution & ROI Modeling: Design and manage Multi-Touch Attribution (MTA) and Marketing Mix Models (MMM) to quantify the impact of marketing across the buyer journey.
  • Causal Inference & Marketing Lift: Apply techniques like propensity score matching and double robust regression to isolate marketing’s incremental impact.
  • Experimentation: Partner with teams to design and analyze A/B tests and incrementality studies that optimize campaign performance.
  • Segmentation & Personalization: Develop audience clusters using first- and third-party data to improve targeting, message relevance, and conversion.
  • Funnel Enablement: Build lead prioritization models and scoring systems to improve sales velocity and conversion.
  • Insight Generation: Translate complex data into clear insights and executive narratives that influence strategy and drive decision-making.
  • Campaign Optimization: Use ML and regression models to improve targeting, spend allocation, and segmentation at scale.
  • Buyer Journey Analytics: Map full-funnel journeys across direct and partner-led paths to identify drop-off points and optimize nurture.
  • Education & Enablement: Build playbooks, dashboards, and training to operationalize analytics and empower stakeholders.
Desired Qualifications
  • Experience in Databricks ecosystem
  • Experience with marketing data pipelines, data governance, or data quality initiatives
  • Experience with experimentation platforms and frameworks
  • Experience building predictive models for marketing and business outcomes
  • Strong communication skills and ability to influence cross-functional teams

Databricks provides a unified data and AI platform built around a lakehouse architecture that blends data lakes and data warehouses. It helps organizations ingest, store, manage, and analyze data from various sources, then apply analytics and machine learning at scale. The platform offers automated ETL, secure data sharing, and high-performance analytics, with built-in support for AI workloads and model deployment. Unlike traditional single-purpose data stores, Databricks combines data engineering, data science, and business analytics in one system, aiming to streamline data workflows and make insights readily actionable. Its goal is to enable businesses to manage data more efficiently, accelerate insight generation, and deploy AI and analytics across diverse teams through a subscription-based platform and professional services.

Company Size

10,001+

Company Stage

Debt Financing

Total Funding

$27.1B

Headquarters

San Francisco, California

Founded

2013

Simplify Jobs

Simplify's Take

What believers are saying

  • Neurolabs, UiPath, and RESAAS expand Databricks into vertical data products and automation.
  • Lakewatch and Lakebase broaden Databricks into security and agentic AI infrastructure.
  • APJ revenue grew over 85% year over year, supporting aggressive regional expansion.

What critics are saying

  • Snowflake and Microsoft Fabric compress Databricks' standalone warehouse and analytics expansion.
  • Hyperscalers can bundle native data, BI, and AI tools below Databricks pricing.
  • Partner ecosystems can reroute workflow control away from Databricks, weakening pricing leverage.

What makes Databricks unique

  • Databricks unifies lakehouse analytics, ETL, machine learning, and generative AI on one platform.
  • Unity Catalog provides governed access, lineage, and Delta Sharing across cloud environments.
  • Google Cloud availability completes Databricks' AWS, Azure, and GCP hyperscaler coverage.

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Your Connections

People at Databricks who can refer or advise you

Benefits

Extended health care including dental and vision

Life/AD&D and disability coverage

Equity awards

Flexible Vacation

Gym reimbursement

Annual personal development fund

Work headphones reimbursement

Employee Assistance Program (EAP)

Business travel accident insurance

Paid Parental Leave

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

0%
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