Staff Data Scientist
Staff Data Scientist
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Job Description
Job description
Who We Are
Verve has created a more efficient and privacy-focused way to buy and monetize advertising. Verve is an ecosystem of demand and supply technologies fusing data media and technology together to deliver results and growth to both advertisers and publishersno matter the screen or location no matter who what or where a customer is. With 30 offices across the globe and with an eye on servicing forward-thinking advertising customers Verves solutions are trusted by more than 90 of the United States top 100 advertisers 4000 publishers globally and the worlds top demand-side platforms. Learn more at.
About the Role
In this role you will work closely with product engineering and other teams collaborate with other Data Science team and with theMachine Learning Engineers to engineer prototypes into solutions.
Domain
In this role your main focus would be on our Audience generation and insight projects
Audience generation: ML for embedded targets audience privacy first approaches Composite AI agents etc..
Audience insight - describe audience composition and characteristics
Adhoc analysis - support business request to better understand our data assets when data is not readily available from our BI tools
Support sales pitch - provided valuable extra insight to augment the value proposition for key accounts
Research and Development
Our Data Science role includes the following responsibilities:
Research and development of cutting edge Machine Learning systems models and schemes in many different areas of Adtech
Develop real-time algorithms for audience creation and segmentation
Discover insights/patterns in our customers from various data sources such as exchange data behavioural data location data 1 and 3rd party data assets
Design experiments oversee A/B testing evaluate the quality of derived assets and continuously monitor model performance
Create proof of concepts and data science prototypes
Search and select appropriate data sets
Perform statistical analysis and use results to improve models
Identify differences in data distribution that could affect model performance in real-world situations
Visualize data for deeper insights
Analyze the use cases of ML algorithms and ranking them by their success probability
Understanding when your findings can be applied to business decisions
Reducing business problems into Machine Learning problems and opportunities
Verifying data quality
Collaborative Work
Work closely with product engineering and sales teams to drive the use of Data Science across the Verve Group
Collaborate with our Exchange Data Science team
Collaborate with Machine Learning Engineers to engineer prototypes into solutions
Job requirements
What You will bring
8 years experience working as a Data Scientist in industry (preferably in advertising) is a must
A postgraduate degree in a relevant quantitative field (e.g. applied mathematics statistics engineering computer science physics operations research economics behavioral sciences). PhD is a strong plus
Fluent in statistical analysis data mining and machine learning
Proficient in Python SQL PySpark TensorFlow (TfLite) Sklearn Keras and Pytorch
Enthusiasm for solving interesting problems
Willingness to learn and work in a team-oriented and constantly changing environment.
Nice to have
Previous experience in
Audience creation and insight
(Highly imbalanced) classification problems
Data asset identification to feature engineering
Classification and neural network
Regularisation Feature selection and hyperparameter tuning
What we also work with
We work with a wide range of tools technologies and processes. The right candidate should have willingness to learn new technologies. In this role is you will get hands-on experience with many established and emerging technologies:
Framework:
Metaflow (or similar)
Modeling framework: Tensorflow Keras pyTorch
Hyperparameter tuning framework: HyperOpt Kerastuner ..
MlFlow
Technologies:
GCP and/or AWS (e.g. logExplorer Cloud function Cloud scheduler)
BigQuery
DevOps tooling:
Airflow (or similar)
Grafana (or similar)
Jupyterhub (or similar)
Other:
Challenging constraints (Sparse data assets Privacy first constraints low latency for inferences)
Efficient work with Big Data (wrangling modeling low latency inference shuffling issue)
Developing data-driven products.
WHAT WE OFFER
Be part of a multicultural team that is bringing advertising to the next level
You will learn and evolve in an empowering environment characterized by entrepreneurial actions
Responsibility independence and an opportunity to participate in projects that have a significant impact on Verves success
3 Wellness days per year (in Q1 Q2 & Q3) and Employee Assistance Program to help you maintain your well-being
Enhance your professional skills with a yearly training budget and improve your language skills through German and/or English classes
Work and Travel Program (monthly raffle after 2 years of employment)
We are eager to build a great team together and we appreciate your help through our Employee Referral Bonus
Align your interests with the companys success and take part in our Employee Shares Purchase Plan
You will be entitled to 19 holidays per year in addition to any of the public/bank holidays
Personalized Benefits Platform; with a budget of 4100 INR/month you can choose the benefits that fit you best from the following options:
Mobility and travel
Entertainment and food
Fitness and healthcare
Enjoy food and beverage benefits with colleagues and have fun during team events
Medical insurance for self and family
Verve provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal state or local laws.
#LI-Hybrid
All done!
Your application has been successfully submitted!
Required Experience:
Staff IC
Employment Type
Full-Time
