Job VC
Data Scientist
Technologies
Description
PwC
is a global network of more than
370,000 professionals in 149 countries
that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.
Join PwC's
Data & AI team
and help design and deliver the
AI and machine learning solutions
that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from
junior to senior Data Scientists
.
Python
is the core skill we expect. Depending on your strengths, you may focus on
machine learning
,
statistical modelling
,
NLP
,
computer vision
, or
GenAI
. Many roles also include "full-solver" flexibility — contributing where needed, including
experimentation
,
prototyping
,
deploying models
, or working
end-to-end on AI use cases
using modern platforms (including
Microsoft technologies
where relevant).
What You'll Do:
Build AI That Solves Real Problems:
Design, develop, train, and evaluate
machine learning
and
statistical models
across a wide range of business challenges.
Turn Messy Data Into Insights:
Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform
feature engineering
,
data preprocessing
, and selection to maximize model performance.
Push the Boundaries With GenAI & NLP:
Design and implement solutions leveraging
Large Language Models
,
Retrieval-Augmented Generation (RAG)
, and
NLP
techniques.
Experiment Rigorously, Deploy Confidently:
Collaborate with
data engineers
and platform teams to move models from
notebook to production
, monitor performance over time, and support continuous
retraining and improvement
.
Work Directly With Clients:
Collaborate with clients across
Western Europe
and the
USA
to understand their business challenges, frame problems as
data science opportunities
, and communicate findings clearly.
Stay Ahead of the Curve:
Keep up with the latest in
AI/ML research
, emerging techniques, and new tools.
Who We're Looking For:
Programming Skills (Key Requirement):
Strong programming skills in
Python
(e.g.
scikit-learn
,
TensorFlow
,
PyTorch
,
pandas
,
NumPy
,
Hugging Face
,
LangChain
). The ability to write
clean, maintainable, and reproducible code
is essential.
Machine Learning:
Demonstrated hands-on experience building, training, and evaluating
ML models
. Strong understanding of supervised and unsupervised learning techniques,
model selection
,
hyperparameter tuning
, and
cross-validation
.
Statistics & Mathematics:
Understanding of core statistical concepts, probability, and linear algebra.
NLP & GenAI (Highly Valued):
Experience with natural language processing, text analytics, large language models, prompt engineering,
RAG architectures
, or other
GenAI
techniques.
Computer Vision (Nice to Have):
Experience with
image processing
,
object detection
,
visual reasoning
, or satellite imagery analysis is an advantage.
Data Handling:
Proficiency in
SQL
and experience with
data wrangling, cleaning, and transformation.
Cloud & MLOps (Nice to Have):
Experience with
cloud platforms
(preferably
Azure
: Databricks, Azure ML, Synapse) or similar services on
AWS/GCP
is an advantage.
Professional Background:
At least
2–3 years
of professional experience in
data science, machine learning, applied research
, or similar
analytical roles
.
Language Skills:
English at
B2 level
or higher.
Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html
is a global network of more than
370,000 professionals in 149 countries
that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.
Join PwC's
Data & AI team
and help design and deliver the
AI and machine learning solutions
that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from
junior to senior Data Scientists
.
Python
is the core skill we expect. Depending on your strengths, you may focus on
machine learning
,
statistical modelling
,
NLP
,
computer vision
, or
GenAI
. Many roles also include "full-solver" flexibility — contributing where needed, including
experimentation
,
prototyping
,
deploying models
, or working
end-to-end on AI use cases
using modern platforms (including
Microsoft technologies
where relevant).
What You'll Do:
Build AI That Solves Real Problems:
Design, develop, train, and evaluate
machine learning
and
statistical models
across a wide range of business challenges.
Turn Messy Data Into Insights:
Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform
feature engineering
,
data preprocessing
, and selection to maximize model performance.
Push the Boundaries With GenAI & NLP:
Design and implement solutions leveraging
Large Language Models
,
Retrieval-Augmented Generation (RAG)
, and
NLP
techniques.
Experiment Rigorously, Deploy Confidently:
Collaborate with
data engineers
and platform teams to move models from
notebook to production
, monitor performance over time, and support continuous
retraining and improvement
.
Work Directly With Clients:
Collaborate with clients across
Western Europe
and the
USA
to understand their business challenges, frame problems as
data science opportunities
, and communicate findings clearly.
Stay Ahead of the Curve:
Keep up with the latest in
AI/ML research
, emerging techniques, and new tools.
Who We're Looking For:
Programming Skills (Key Requirement):
Strong programming skills in
Python
(e.g.
scikit-learn
,
TensorFlow
,
PyTorch
,
pandas
,
NumPy
,
Hugging Face
,
LangChain
). The ability to write
clean, maintainable, and reproducible code
is essential.
Machine Learning:
Demonstrated hands-on experience building, training, and evaluating
ML models
. Strong understanding of supervised and unsupervised learning techniques,
model selection
,
hyperparameter tuning
, and
cross-validation
.
Statistics & Mathematics:
Understanding of core statistical concepts, probability, and linear algebra.
NLP & GenAI (Highly Valued):
Experience with natural language processing, text analytics, large language models, prompt engineering,
RAG architectures
, or other
GenAI
techniques.
Computer Vision (Nice to Have):
Experience with
image processing
,
object detection
,
visual reasoning
, or satellite imagery analysis is an advantage.
Data Handling:
Proficiency in
SQL
and experience with
data wrangling, cleaning, and transformation.
Cloud & MLOps (Nice to Have):
Experience with
cloud platforms
(preferably
Azure
: Databricks, Azure ML, Synapse) or similar services on
AWS/GCP
is an advantage.
Professional Background:
At least
2–3 years
of professional experience in
data science, machine learning, applied research
, or similar
analytical roles
.
Language Skills:
English at
B2 level
or higher.
Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html