Job VC
Senior Data Scientist (AdTech / DSP Systems)
Technologies
Description
About the role
We are looking for a
Senior Data Scientist
to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.
This is not a “campaign optimization” role. You will work on the
core decision-making systems (DSP level)
— where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.
You will be shaping the
“brain” of the platform
: a set of interconnected systems where small improvements can have a large business impact.
What you’ll work on
Pricing & Budget Scalability
Scale budgets while maintaining performance and controlling overspend
User Selection Optimization
Improve CVR through smarter targeting and traffic selection
Exploration Efficiency
Reduce wasted spend while preserving learning
Incrementality Measurement
Measure true lift vs attributed performance
Fraud Detection & Filtering
Improve traffic quality and filtering strategies
What we expect from you
System-level thinking
Ability to reason about
interacting systems
, not isolated models
Understanding of:
auction dynamics
bidding vs pacing trade-offs
feedback loops between models
Seeing problems beyond segmentation or heuristics
Strong experimentation mindset
Designing experiments, not just running A/B tests
Experience with:
metric design (proxy vs north star)
online vs offline evaluation gaps
interference and auction effects
Ability to translate system changes into measurable impact
Ownership & impact
Proven track record of driving
business impact
, not only building models
Ability to explain:
expected vs actual impact
why results differ
Performance accountability mindset
AdTech domain understanding
Solid understanding of:
targeting vs bidding vs supply dynamics
Experience working close to
DSP / auctions/pricing systems
Collaboration maturity
Ability to work across DS, MLE, and Product
Understanding trade-offs and constraints
Experience making decisions in ambiguous environments
Core responsibilities
Turn ambiguous problems into
testable hypotheses
Design and run
offline analysis + online experiments
Use
intermediate metrics
to understand system behavior
Build prototypes and iterate quickly
Identify where
system-level improvements
are required
Collaborate across teams to drive end-to-end impact
Requirements
5+ years in Data Science / Machine Learning
Strong experience in
high-frequency systems
(AdTech / FinTech / similar)
Python & SQL proficiency
Experience with big data tools (Spark, Snowflake, etc.)
Strong ML background (TensorFlow, PyTorch, or similar)
Solid foundation in:
probability
statistics (frequentist / Bayesian)
causal inference
Master’s or PhD in a quantitative field
Nice to have
Experience with
DSP / auctions / pricing systems
Experience with
large-scale experimentation
We are looking for a
Senior Data Scientist
to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.
This is not a “campaign optimization” role. You will work on the
core decision-making systems (DSP level)
— where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.
You will be shaping the
“brain” of the platform
: a set of interconnected systems where small improvements can have a large business impact.
What you’ll work on
Pricing & Budget Scalability
Scale budgets while maintaining performance and controlling overspend
User Selection Optimization
Improve CVR through smarter targeting and traffic selection
Exploration Efficiency
Reduce wasted spend while preserving learning
Incrementality Measurement
Measure true lift vs attributed performance
Fraud Detection & Filtering
Improve traffic quality and filtering strategies
What we expect from you
System-level thinking
Ability to reason about
interacting systems
, not isolated models
Understanding of:
auction dynamics
bidding vs pacing trade-offs
feedback loops between models
Seeing problems beyond segmentation or heuristics
Strong experimentation mindset
Designing experiments, not just running A/B tests
Experience with:
metric design (proxy vs north star)
online vs offline evaluation gaps
interference and auction effects
Ability to translate system changes into measurable impact
Ownership & impact
Proven track record of driving
business impact
, not only building models
Ability to explain:
expected vs actual impact
why results differ
Performance accountability mindset
AdTech domain understanding
Solid understanding of:
targeting vs bidding vs supply dynamics
Experience working close to
DSP / auctions/pricing systems
Collaboration maturity
Ability to work across DS, MLE, and Product
Understanding trade-offs and constraints
Experience making decisions in ambiguous environments
Core responsibilities
Turn ambiguous problems into
testable hypotheses
Design and run
offline analysis + online experiments
Use
intermediate metrics
to understand system behavior
Build prototypes and iterate quickly
Identify where
system-level improvements
are required
Collaborate across teams to drive end-to-end impact
Requirements
5+ years in Data Science / Machine Learning
Strong experience in
high-frequency systems
(AdTech / FinTech / similar)
Python & SQL proficiency
Experience with big data tools (Spark, Snowflake, etc.)
Strong ML background (TensorFlow, PyTorch, or similar)
Solid foundation in:
probability
statistics (frequentist / Bayesian)
causal inference
Master’s or PhD in a quantitative field
Nice to have
Experience with
DSP / auctions / pricing systems
Experience with
large-scale experimentation