About the role
We’re accepting these challenges by applying data, algorithms and machine learning to problems in logistics, routes, personalization, search, pricing, experimentation and more. Our Data Science team is at the heart of this effort and is an essential ingredient in Beat’s aggressive growth plan and vision for the future.
As a member of the Experimentation team, you will take on some of our biggest challenges and your work will impact the entire Beat experience. Our team moves very fast, so you’ll have the opportunity to make an immediate difference.
The experimentation squad’s primary objective is to democratise data driven decision making and accelerate adoption of experimentation in the organisation. You will be working closely with data analysts, engineers, designers and product managers to drive a culture of causal reasoning, and push for features that improve the design, analysis, and interpretation of experiments.
Our remote workforce works East Europe Timezone hours (10am – 6pm) and therefore we will need you to be located within UTC to UTC+3 to reasonably overlap with your team members’ work schedule. With the various tools and communication technologies we’re using, you’ll feel connected to your team. You always have the option to travel to our headquarters for meetings, events, and team bonding—or you can join virtually. Whatever works best for you and your work style.
What you’ll do day in day out:
- Lead the effort in building robust and efficient causal inference methodologies in our experimentation platform to aid decision making.
- Employ advanced statistical methods to help decision makers draw detailed conclusions on their experiments.
- Advise other product and business teams across Beat and help them design and run experiments.
- Evangelise experimentation and data driven decision making within Beat by conducting workshops, sharing knowledge and promoting adoption of good statistical practices.
- Leverage data to find business opportunities and develop creative solutions to solve those by employing data science methods such as machine learning, optimisation algorithms etc.
- Be the changemaker by identifying, and challenging status-quo while advocating use of statistically sound decision making processes.
- Work with structured and semi-structured data from different data sources and different products.
- Mentor other data analysts and data scientists within the team.
What you need to have:
- Educational background in Maths, Statistics, Data Science, Computer Science, Engineering or other quantitative discipline or equivalent experience.
- At least 3 years of hands-on experience in machine learning methodologies and predictive analytics to solve business and user problems using Python or R.
- Experience with experimentation – designing experiments, using causal inference methods to draw conclusions.
- Proficiency in R/Python, and SQL.
- Additional competence in data engineering, Scala, noSQL, Apache Hadoop, Spark or Tensorflow, is appreciated but not required.
- Excellent grasp of concepts of statistics, causality, and terms such as statistical significance, interference effects, biases, variance etc.
- Experience with exploratory data analysis, testing and modelling.
- Self-initiative – be able to independently take initiatives without much direction.
- Deep belief in data and ability to rally people behind your findings/recommendations.
What’s in it for you:
- Competitive salary package
- Flexible working hours
- High tech equipment and top line tools
- Working in a hyper-growth environment, you will enjoy numerous learning and career development opportunities
- A great opportunity to grow and work with the most amazing people in the industry.
- Being part of an environment that offers challenging goals, autonomy and mentoring, which creates incredible opportunities, both for you and the company.