Data Scientist Offline

On behalf of our Client from Singapore/UK, Mobilunity is looking for a Data Scientist.

Our client is a retail technology business working with local shops, national labels, and global brands operating in physical retail. Built on a unique set of technologies and AI, their platform empowers retailers and Consumer Packaged Goods (CPG) manufacturers across the globe to drive growth in their markets.

Their platform is connected to 20.000+ Points of Sales across 40+ countries ranging from Big Retailer Chains like New Look, Samsonite, and Lego to small mom&pop corner shops in South-East Asia. They are data-enthusiasts and processing and creating value on top of around 350 million granular shopping receipt data every year and growing.

The company has built unique ML algorithms in the area of NLP parsing, Data Enrichment, and Predictions to create better value out of our vast dataset and make it usable for Retailers, Brand Companies, Data Clients, Advertisers and Tech Partners.

Responsibilities:

Dive into our transactional dataset of millions of retail transaction data from offline stores – enriching it with additional properties and creating downstream solutions for our platform and its products

Build and enhance solutions for large retail and consumer goods brands and thousands of independent grocery merchants in an organisation of data engineers, software engineers, and business users

Own and drive the data science roadmaps with product leads and data analysts to tackle problems such as product data enrichment, categorisation, demand forecasting, pricing, product recommendations, customer understanding, and promotion evaluation

Build and grow company-wide capabilities around natural language, representation learning, geospatial, and time series analysis

Must have skills:

5-7 years of experience in product data science or machine learning roles

Experience in research and development of scalable models for production

Bachelor’s degree or above, majoring in related technical disciplines

Proficiency in Python and its common data science libraries

Strong working knowledge in SQL and RDBMS e.g. MySQL or Snowflake

Experience with DevOps tools like Git / Bitbucket

Experience in machine learning deployment in cloud environments

Experience in MLOps tools like Metaflow, MLflow, WandB, Optuna

Familiar with deep learning frameworks e.g. PyTorch and algorithms e.g. CNN, LSTM

Familiar with commonly used NLP algorithms and advances, such as word2vec or language models

Experience in NLP of non-roman languages/scripts e.g. Thai

Familiar with probability theory, statistical analysis, and outlier detection

Competence in data science models like dimensional reduction, clustering, classification etc

Nice to have skills:

Experience in developing and producing rising recommender systems

Experience in causal inference techniques especially for marketing technology use cases around promotion campaign planning & evaluation

Industrial experience in data science developments for online & offline retail and/or Consumer Goods/FMCG

In return we offer:

The friendliest community of like-minded IT-people

Open knowledge-sharing environment – exclusive access to a rich pool of colleagues willing to share their endless insights into the broadest variety of modern technologies

Mobilunity Medical Insurance program designed to attend our teams’ needs

Paid vacations and sick leaves, including 5 paid days per year that don’t require a sick note

Fair salary and 100% taxes coverage – don’t worry about possible taxes raise – we will get you covered

Perfect office location in the city-center (900m from Lukyanivska metro station with a green and spacious neighborhood) or remote mode engagement: you can choose a convenient one for you, with a possibility to fit together both

No open-spaces setup – separate rooms for every team’s comfort and multiple lounge and gaming zones on all of the 3 floors

English classes in 1-to-1 & group modes with elements of gamification

Neverending fun: sports events, tournaments, music band, multiple affinity groups