Our partner is a low-code data science platform. They help businesses to make data-driven decisions without coding or prior algorithms knowledge.
We are looking for a Data Analyst who will help them bring value to their customers by discovering insights hidden in vast amounts of data and building machine learning models for our clients.
Your primary focus will be on working with the client’s data, applying data mining techniques, and building pipelines to implement forecasting models. You will be working directly with the clients to understand the business problem and the best way to bring value.
Duties and Responsibilities
— Direct communication with the clients across various industries to solve business problems
— Data analysis, pipeline implementation, and model creation based on clients’ data and problems
— Creation of end-to-end pipelines for clients, educating clients on how to use the datrics.ai platform and how to utilize the created pipelines
— Ad-hoc research, design, and implement algorithms for vertical use cases
— Contribute to the product concepts planning from a data analyst perspective, help drive platform development from the user’s standpoint
1. Education and degree:
— Masters Degree in a quantitative field (Math, Statistics, Computer Science, Engineering, Data Science, Operations Research, etc.).
2. Specialized knowledge:
— Applied Statistics (Exploratory Data Analysis and Distributions Fitting, Inference on Populations, Regression Analysis, Causality)
— Predictive analytics (Classification and Regression Models, Time-series analysis and forecasting, Survival or duration analysis as a plus)
— Design of the predictive research
3. Good understanding of:
— Data Mining concepts (Clustering, Frequent Pattern Mining, Outliers Detection)
— Machine Learning Concepts (Supervised/Unsupervised learning, Models assessment, and comparison)
— Machine Learning Algorithm (Tree-based models, Linear Models, Instance-based models, etc.)
4. Ability to effectively communicate in written documents and oral briefings regarding studies initiation, justification of methods selected, results, conclusions, and recommendations.
5. Python programming skills
6. Basic knowledge in :
— Databases (SQL and NoSQL)
— Development Tools (SVN, Git)
7. Understanding of software development company functioning
8. Understanding of software development life cycles
Skills & abilities:
— English intermediate strong level or higher
— Team playing and result orientation skills
— Client orientation
— Communication skills