About Affinity
Affinity is pioneering new
frontiers in AdTech: developing solutions that push past today’s limits and
open up new opportunities. We are a global AdTech company helping publishers
discover better ways to monetize and enabling advertisers to reach the right
audiences through new touchpoints. Operating across 10+ markets in Asia, the
US, and Europe with a team of over 450 experts, we are building privacy-first
ad infrastructure that opens up opportunities beyond the walled gardens.
Role: Director, Data Science
Work Location: Mumbai (Malad)
About Role:
We are
seeking a Head of Data Science to lead AI/ML initiatives across all our business
units, driving measurable impact in digital advertising through sophisticated
algorithms and team leadership. This high-impact role combines hands-on
technical expertise with strategic vision, directly influencing millions in
advertising revenue. You'll collaborate with C-level executives while building
industry-leading AdTech solutions and establishing measurement frameworks that
set new standards for performance. We're looking for a technical visionary who
can balance algorithm development with strategic leadership across our global
advertising ecosystem.
Roles & Responsibility:
- Think Future, Build present – Create scalable solutions addressing current challenges while building frameworks for growth.
- Design AI/ML
algorithms for performance and programmatic advertising platforms with emphasis
on floor price optimization and yield management.
- Build bid prediction
models and supply path optimization algorithms to maximize publisher revenue.
- Develop algos and
models which help various targeting for real-time ad delivery.
- Implement audience
segmentation and lookalike modelling for brand campaigns.
- Think Data – Derive data insights from processes, products, and integrations to achieve efficiency and performance goals.
- Establish KPI-driven
measurement frameworks focused on incrementality gains and attribution accuracy.
- Build predictive
models for campaign forecasting and budget optimizations.
- Develop fraud
detection algorithms and brand safety classification systems.
- Analyze data and identify trends, patterns, and anomalies in model behavior.
- Ensure data privacy
compliance (GDPR, CCPA) and implement secure data handling practices and
participate in AI policy-making.
- Think Technology – Build enterprise-grade ML/ AI architectural solutions that drive real value, and measurable business impact.
- Develop MLOps and data
pipelines from ad serving events, implementing real-time feature engineering
and model serving infrastructure catering to billions of ads.
- Build predictive models, dashboard / reports for performance monitoring.
- Conduct rigorous A/B
testing and statistical analysis to validate algorithmic improvements and
business impact with explainable-AI algorithms.
- Think
Collaboration - Partner with cross-functional teams (stakeholders, product, developers and business) to deliver models, dashboards, solutions that drive revenue KPIs
- Think Leadership -
Drive strategic ML/AI vision across business units, build and scale
high-performing teams, and own P&L responsibility for data science
investments. Collaborate with fellow leaders to establish company-wide AI
governance and present ROI metrics to executive leadership.
Required Skills:
- 8+ years’
experience as Data Scientist with 3+ years in advertising technology and KPI
optimisation
- MS/PhD in Computer Science, Statistics,
Mathematics, or related quantitative field.
- Technical Expertise:
- Programming: Advanced Python, SQL, with experience
in Hadoop and Apache Spark for large-scale data processing.
- ML/ AI stack: Tensorflow, PyTorch, XGBoost, LLMs, scikit-learn
for time-series forecasting, recommendation systems, NLP optimisation, and
causal inference. Exposure to ML, NN, GenAI algorithms.
- Infrastructure: Cloud platforms (GCP/Azure/AWS),
MLOps, real-time model inference, feature stores, and ML pipeline orchestration
- Visualization: Power BI, Looker, Jupyter Notebooks,
and custom dashboard developments
- Production Systems: Building scalable ML systems
with real-time performance monitoring and A/B testing frameworks.
- Domain Knowledge
- Deep knowledge of digital marketing and advertising
technologies and concepts like RTB protocols, header bidding, programmatic
advertising ecosystems, and Google ADX.
- Understanding of Ad Server APIs, DSP/SSP
integrations, DMP usage, auction dynamics, attribution modelling, conversion
tracking, and audience segmentation.
- Proven track record of optimising AdTech KPIs
with demonstrated results.
- Leadership -
Strong communication skills for technical and executive audiences with ability
to translate KPI improvements into business impact.