от 200 000 ₽
до 300 000 ₽
Требуемый опыт работы: 3–6 лет
Полная занятость, удаленная работа
SegmentStream — AI-powered data intelligence platform built for advanced digital marketing teams. Our mission is to make artificial intelligence technologies more accessible for marketing teams to achieve their goals faster without developers and data scientists.
We’re looking for an experienced Data Scientist to function as a key member of SegmentStream’s Data team to develop, validate, and maintain predictive modeling solutions for a variety of unique problems in the marketing attribution and optimisation space.
As a Data Scientist, you’ll be applying machine learning and statistical techniques on vast data sets to create and support data-driven products and business insights.
SegmentStream — AI-powered data intelligence platform built for advanced digital marketing teams. Our advanced SaaS platform helps companies to unify digital marketing and sales data from various data sources into their own data warehouse and apply AI-powered marketing attribution and automation to increase Return on Ad Spend across all the channels.
The product is used by over 100 customers around the world. We analyse multi-million dollar budgets and process terabytes of data every day. We are proud to be VC-backed by one of the world’s leading startup accelerators - Techstars, as well as some biggest names in the B2B SaaS world, including the founders of Pipedrive, Dynamic Yield, and other great companies.
Our researches on the smart application of the AI for marketing analytics and algorithms for building sophisticated attribution models based on machine learning are published by the top analytical resources in the world.
What you’ll do:
- Develop machine learning models to create innovative solutions to problems in the attribution and marketing analytics industry;
- Continually improve the accuracy and efficiency of current ML models;
- Prepare SQL for data preprocessing and feature mining;
- Prepare created ML algorithms for deployment into our live production environment;
- Assist in A/B-test design and hypothesis testing of marketing campaigns;
What we are looking for:
- 2 + years of experience with Python for statistical analysis, data visualisation, and predictive modeling;
- 2 + years of experience with SQL for data analysis;
- Strong math skills (e.g. statistics, algebra);
- Experience in solving classification and regression problems on structured data;
- Working knowledge of popular machine learning algorithms, such as regression, clustering, random forest, and gradient boosting;
- Experience in implementing a created ML models in a production environment;
- Ability to understand a business challenge from the management team and design a proper technical solution;
- Good communication skills (both verbal and written);
- Good English (B2 or above);
- Experience in marketing attribution modeling or CRM modeling (churn, cross-sell, etc.);
- Experience with the cloud data warehouses and ML technologies such as Google BigQuery, BigQuery ML, Amazon Cloud, etc.;
- Experience working with tools like Airflow and getdbt;
- Experience in A/B-test design and hypothesis testing;
- You have a Kaggle or GitHub with an open-source work that you are proud to share;
- Unique and high-quality SaaS product that solves a massive problem for a huge market;
- A vast portfolio of enterprise customers around the globe including the UK, US, Canada, Australia, and lots of European countries;
- VC-backed by top investors & angels, including TechStars, founders of Pipedrive, Dynamic Yield, and other great SaaS entrepreneurs;
- Fast-growing, fully distributed, and international team of smart people who not only love what they do but also really good at it;
- A great company culture that is embracing functional ownership, entrepreneurial mindset, and personal growth;
- Full responsibility from day one and being part of our results-driven working environment;
- Competitive salary plus attractive stock compensation package;
- A lot of opportunities for future career growth within the company;