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Data Scientist

Acxiom Global Service Center Polska sp. z o. o

  • Silesian

    Silesian
  • offer expired 9 days ago
  • contract of employment
  • full-time
  • specialist (Mid / Regular), senior specialist (Senior)
  • home office work, hybrid work
  • More than one vacancy
  • remote recruitment
  • запрошуємо працівників з України
  • Робота для іноземців
    без польської
ukrainian-friendly-overlay
Запрошуємо працівників з України
Роботодавець відкритий для працевлаштування громадян України

Technologies we use

Expected

  • XG Boost

  • Python

  • R

  • Spark

  • Julia

  • scikit-learn

  • MLlib

  • ETL

  • SQL

Optional

  • AWS Sagemaker

  • Airflow

  • KubeFlow

  • Google AI/ML

  • CI/CD/MLOps

  • Kubernetes

  • Docker

  • ECS/EKS

  • Tensorflow

  • Keras

  • Google Cloud Platform

Operating system

About the project

At Acxiom, our vision is to transform data into value for everyone. Our data products and analytical services enable marketers to recognize, better understand, and then deliver highly applicable messages to consumers across any available channel. Our solutions enable true people-based marketing with identity resolution and rich descriptive and predictive audience segmentation. We are seeking an experienced Data Scientist with a versatile skill set to undertake data science supporting the development of next-generation data product. As part of the Data Science and Analytics Team, the Data Scientist will lead the charge in developing machine learning and statistical models to support and expand the Audience Propensities product suite for our domestic and global businesses.

Your responsibilities

  • Build expert knowledge of the various data sources brought together for audience propensities solutions – survey/panel data, 3rd-party data (demographics, psychographics, lifestyle segments), media content activity (TV, Digital, Mobile, Automotive), and product purchase or transaction data

  • Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to develop new audience propensities & analytical data products or improve the performance/quality of existing audience propensities and data products

  • Build, evaluate and optimize models which incorporate machine learning and artificial intelligence

  • Be a thought leader and champion for adoption of new technologies and enable migration to new cloud based Machine Learning stack

  • Collaborate with internal and external stakeholders to understand business goals and product economics, and identify relevant KPIs to assess product in-market performance

  • Collaborate with other data scientists and team leads to define project requirements including data sources, algorithms, and implementation

  • Partner with Product and Engineering teams to transition development projects to production systems

  • Effectively communicate complex data science concepts to marketing and business audiences

Our requirements

  • Solid experience in leveraging data science and modeling methods. Experience in AdTech/MarTech space is a plus.

  • Previous work with digital marketing datasets will be a plus

  • Experience with applying statistics and data science tools on large datasets. Extensive experience with data preparation (normalization, scaling, etc.) for modeling

  • Working knowledge of supervised vs. unsupervised learning algorithms, including linear/logistic regression, neural networks/deep learning techniques, SVM, decision trees (bagging, random forests, boosting), XG Boost, clustering, regression, and dimensionality reduction techniques

  • Strong skills on model training approaches, hyperparameter tuning, and model evaluation approaches

  • 2+ years of experience building, testing and deploying production ready models in python, R, spark, Julia or similar languages and experience using Scikit learn, MLlib or similar packages

  • 2+ years of experience building ETL transformation, SQL, modeling & mlops pipelines

  • Very good knowledge of English, written and spoken

Optional

  • Experience with E2E ML platform such as AWS Sagemaker, Google AI/ML platform

  • Experience using tools such as Airflow, KubeFlow for model deployment will be a plus

  • Exposure to CI/CD/MLOps - container-based model deployment frameworks using (Kubernetes, Docker, ECS/EKS or similar) will be a plus

  • At least 1 year of experience leveraging Deep Learning, Neural Network based modeling frameworks (Tensorflow, Keras)

  • At least 1 year of experience deploying data/analytical products at scale using Cloud technologies e.g. AWS Sagemaker, Google Cloud Platform, etc.)

This is how we organize our work

Team size

  • 8

This is how we work

  • in house
  • you develop several projects simultaneously
  • agile

Development opportunities we offer

  • conferences in Poland

  • development budget

  • external training

  • industry-specific e-learning platforms

  • support of IT events

What we offer

  • Permanent contract from the very beginning (umowa o pracę)

  • Life-Work balance

  • Multisport/participation in cultural events

  • Lunch+ card which can be used in cafes and restaurants

  • On-site English and/or German classes

  • Training - professional certificates, webinars, classroom trainings

  • Online access to thousands of technical ebooks (Books 24x7, Safari Books Online) and trainings (SkillsSoft)

  • Fun rooms with a pool table, darts, football table, playstation and board games

  • Benefits

  • sharing the costs of sports activities

  • private medical care

  • sharing the costs of professional training & courses

  • life insurance

  • remote work opportunities

  • flexible working time

  • dental care

  • no dress code

  • video games at work

  • coffee / tea

  • pre-paid cards

  • christmas gifts

  • employee referral program

Recruitment stages
1

HR phone screen

2

Technical Interview with TL and the team (Zoom)

3

Decision

Acxiom Global Service Center Polska sp. z o. o

Acxiom is a recognized global leader in marketing services and technology. Company was founded in 1969, headquartered in the United States with offices in Europe, Australia, New Zealand and China. Our data and technology have transformed marketing – giving our clients the power to successfully manage audiences, personalize customer experiences and create profitable customer relationships. We deliver campaigns to 127 countries in more than two dozen different languages.

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