Position: Head of Marketing Data Science
Company: Ciklum
Experience required: 5y
English level: fluent

Responsibilities

Decide when to implement internal solutions and when to use solutions from external providers
Identify best practices from other companies and implement them in Seeking Alpha
Algorithm research, development, evaluation, optimization for audience analysis and personalization
Identifying and deciding on promising research and development directions, balancing short term and long term goals
Recruit, lead and mentor the marketing data analysts, and help with their professional development
Communicate and coordinate with product and business counterparts

Requirements

Successful track record of implementing data science to achieve commercial goals
MSc/Ph.D. in Computer Science, Statistics, Mathematics or other related fields
5+ years of experience as a data scientist or similar role
Experience leading data science projects – a must
Deep technical understanding of underlying DS concepts (not just training models)
Great knowledge of, and hands-on experience with, Python, R, SQL, etc
Experience with unsupervised and semi-supervised clustering algorithms
Experience with structured and unstructured data
Excellent business understanding, problem-solving abilities, and organizational skills
Quick learner, adaptable, with the ability to work in a fast-paced environment
Strong verbal and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
High-level English – a must

Desirable

Economics and Behavioural Economics background
Experience with time series analysis, causal inference analysis, web behavior analytics, NLP, XAI, RL, Collaborative Filtering
Fluent in SQL enough to get the data you need from a warehouse (Vertica, Hive, SparkSQL)
Experience with building end-to-end reusable pipelines from data acquisition to model output delivery
Experience with deploying ML models to a production environment: Experiment tracking, A/B Tests, Model degradation, and more

What's in it for you

Very close cooperation with the client
Possibility to propose solutions on a project
Dynamic and challenging tasks
Ability to influence project technologies
Team of professionals: learn from colleagues and gain recognition of your skills
Low bureaucracy, European management style