- Professional
About Forbes Advisor
Forbes Digital Marketing Inc. is a high-growth digital media and technology company dedicated
to helping consumers make confident, informed decisions about their money, health, careers,
and everyday life.
We do this by combining data-driven content, rigorous product comparisons, and user-first
design — all built on top of a modern, scalable platform. Our global teams bring deep expertise
across journalism, product, performance marketing, data, and analytics.
Job Description:
The Role
We’re hiring a Data Scientist to help us unlock growth through advanced analytics and machine
learning. This role sits at the intersection of marketing performance, product optimization, and
decision science.
You’ll partner closely with Paid Media, Product, and Engineering to build models, generate
insight, and influence how we acquire, retain, and monetize users. From campaign ROI to user
segmentation and funnel optimization, your work will directly shape how we grow.
This role is ideal for someone who thrives on business impact, communicates clearly, and
wants to build re-usable, production-ready insights — not just run one-off analyses.
What You’ll Do
Marketing & Revenue Modelling
• Own end-to-end modelling of LTV, user segmentation, retention, and marketing
efficiency to inform media optimization and value attribution.
• Collaborate with Paid Media and RevOps to optimize SEM performance, predict high-
value cohorts, and power strategic bidding and targeting.
Product & Growth Analytics
• Work closely with Product Insights and General Managers (GMs) to define core metrics,
KPIs, and success frameworks for new launches and features.
• Conduct deep-dive analysis of user behaviour, funnel performance, and product
engagement to uncover actionable insights.
• Monitor and explain changes in key product metrics, identifying root causes and
business impact.
• Work closely with Data Engineering to design and maintain scalable data pipelines that
support machine learning workflows, model retraining, and real-time inference.
Predictive Modelling & Machine Learning
• Build predictive models for conversion, churn, revenue, and engagement using
regression, classification, or time-series approaches.
• Identify opportunities for prescriptive analytics and automation in key product and
marketing workflows.
• Support development of reusable ML pipelines for production-scale use cases in
product recommendation, lead scoring, and SEM planning.
Collaboration & Communication
• Present insights and recommendations to a variety of stakeholders — from ICs to
executives — in a clear and compelling manner.
• Translate business needs into data problems, and complex findings into strategic action
plans.
• Work cross-functionally with Engineering, Product, BI, and Marketing to deliver and
deploy your work.
What You’ll Bring
Minimum Qualifications
• Bachelor’s degree in a quantitative field (Mathematics, Statistics, CS, Engineering, etc.).
• 4+ years in data science, growth analytics, or decision science roles.
• Strong SQL and Python skills (Pandas, Scikit-learn, NumPy).
• Hands-on experience with Tableau, Looker, or similar BI tools.
• Familiarity with LTV modelling, retention curves, cohort analysis, and media attribution.
• Experience with GA4, Google Ads, Meta, or other performance marketing platforms.
• Clear communication skills and a track record of turning data into decisions.
Nice to Have
• Experience with BigQuery and Google Cloud Platform (or equivalent).
• Familiarity with affiliate or lead-gen business models.
• Exposure to NLP, LLMs, embeddings, or agent-based analytics.
• Ability to contribute to model deployment workflows (e.g., using Vertex AI, Airflow, or
Composer).
Why Join Us?
• Remote-first and flexible — work from anywhere in India with global exposure.
• Monthly long weekends (every third Friday off).
• Generous wellness stipends and parental leave.
• A collaborative team where your voice is heard and your work drives real impact.
• Opportunity to help shape the future of data science at one of the world’s most trusted
brands.
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