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Access Finance

Senior Data Scientist

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    Tech Stack / Requirements

    Access Finance AD is an 11-year non-banking financial institution providing credit cards and managing a large portfolio of clients through extensive utilization of machine learning and automation. Currently operating in Bulgaria, Romania, Spain, and Mexico, we are soon expanding into the U.S. market. Our innovative approach and commitment to financial technology set us apart as a leader in the industry.

    In order to keep up with the growing company’s portfolio and business diversity we have an opening for a Senior Data Scientist to join our Credit Risk and Data Science Directorate.

     

    What you would be able to do:

    • Develop, test, deploy and monitor supervised and unsupervised Machine Learning models with no constraints to the modelling techniques, using diverse data sources – telecom data, google analytics data, income and credit history data, bank accounts data, text and voice data, social media data

    • Be part of the development, implementation and support of AI chatbots for customer service – already live in 1 market

    • Work in diverse modelling and AI domains – credit risk, churn prediction, segmentation, sales optimization, collection optimization, customer relationship management, propensity to buy, customer service, Generative AI

    • Practice and further develop the skills needed to support the complete Machine Learning project lifecycle – problem definition, data gathering, data wrangling, model development, validation, deployment and monitoring

    • Make business impact and see the results of your work help the company increase its profit

    • Utilize the already defined data, processes and machine learning pipelines with the opportunity to further develop them.

     

     Requirements:

    • Strong business orientation and willingness to apply machine learning for the purpose of improving the business results

    • 4+ years of experience in the analytics field – machine learning models development and deployment, experience with binary classification problems is considered a strong plus

    • Experience with at least one programming language used for data science – R or Python

    • Experience with relational databases – Microsoft SQL Server or equivalent

    • Experience in any of the following technologies is considered a strong advantage:

     Data visualization tools– Power BI or equivalent

     APIs and machine learning model deployment under APIs

     Microsoft Azure and Azure Pipelines

     Docker

     Kubernetes

     Git

     LLM business applications development

    • Ability to work comfortably and combine data coming from a variety of data sources – relational and non-relational databases, cloud databases, csv and excel files, xml and json files

    • University degree or equivalent standard with a high numeric and/or technical content: data science, artificial intelligence, statistics, mathematics, informatics, software development.

     

     Benefits:

    • A team of senior level people with extensive experience in the field and international acknowledgements;
    • Competitive remuneration
    • Additional health insurance
    • Option for Multisport card at a discount price
    • Work from home option -2 days weekly
    • Free tea/coffee, and fruit are always available. Pizza day and  snacks
    • Newborn baby bonus
    • Opportunity to work, develop and grow in a dynamic environment, targeted at international expansion
    • Friendly and casual work environment.

     

    We are searching for candidates who have the capabilities and are willing to develop into full-stack data scientists to help and support our diverse business operations with Machine Learning and Large Language Models. If you enjoy making decisions, want your work to be recognized and important, and have the skills to bring business value through data science this role might be the best fit for you.

    We encourage you to take a couple of minutes to submit your resume to be considered as the newest member of our professional team.

    We appreciate and thank you for your application. Only short-listed candidates will be contacted.