Data Scientist
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Before you apply
LocationСофия
Work modehybrid
Typefull-time
SeniorityEntry
Experience1+ yrs
Company size1,001–5,000 people
PostedOct 7, 2026 · 1mo ago
Verified live19h ago
At a glanceSummarised by Seekless from the posting.
1+ year of hands-on experience in data science, machine learning, or advanced data analytics
Basic understanding of the Software Development Lifecycle (SDLC) and Agile/Scrum project frameworks
Experience in the end-to-end data pipeline including data exploration, preprocessing, feature engineering, model training, validation, and evaluation
Familiarity with project management and code management tools (e.g., Jira, GitHub)
Understanding of data science documentation and workflows (Jupyter Notebooks, model performance metrics, data dictionaries)
Ability to analyze business requirements and translate them into data-driven solutions
Strong proficiency in Python and core data science libraries (Pandas, NumPy, Scikit-learn)
Solid understanding of databases and SQL basics
Familiarity with exploratory data analysis (EDA) and data visualization tools (Matplotlib, Seaborn, Tableau, or PowerBI)
Basic knowledge of version control systems (specifically Git)
Fundamental understanding of core ML concepts (supervised vs. unsupervised learning, regression, classification, clustering)
Strong analytical thinking, mathematical intuition, and high attention to detail
Good problem-solving skills and ability to challenge assumptions about data and model behavior
Ability to work both independently and collaboratively with engineers and business stakeholders
Good written and verbal communication skills in English
Proactive attitude and willingness to stay updated on AI/ML trends
Exposure to modern Generative AI techniques, Large Language Models (LLMs), or prompt engineering
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch)
Familiarity with processing large-scale datasets using cloud environments or distributed computing (e.g., basic Spark/Databricks)
Basic knowledge of ML deployment concepts or MLOps pipelines (e.g., MLflow, Docker)
Skills
Python
Pandas
NumPy
Scikit-learn
SQL
Git
Jupyter
Matplotlib
Seaborn
Tableau
PowerBI
Jira
GitHub
TensorFlow
PyTorch
Spark
Databricks
MLflow
Docker
Benefits
Health insurance
Flexible hours
Home office
Strength. Care. Growth.
Did you know that A1 Bulgaria is working on international projects as well?
Our wide portfolio has long past the telecom services, and we are now offering digital solutions to millions of corporate, public, and private customers.
State-of-the-art technology, the latest innovations, and extremely talented professionals in various areas help us deliver the best-in-class products, services, and customer experience.
You’ll know A1 Bulgaria is the right place for you if you are driven by:
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Opportunities to learn and build your career.
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Meaningful work in a stable and fast-paced company.
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Diversity of people, projects, and platforms.
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A supportive, fun, and inspiring place to work.
Would you like to join us?
Boyan Tsanev is looking for a new team member.
Your daily routine would include:
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Collecting, exploring, and preprocessing data to ensure quality, consistency, and readiness for analysis and model development.
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Performing exploratory data analysis (EDA) to identify trends, patterns, and actionable insights.
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Developing, training, validating, and evaluating machine learning models to address business challenges.
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Engineering and selecting relevant features to improve model performance and predictive accuracy.
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Collaborating with business stakeholders to understand requirements and translate them into data-driven solutions.
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Working closely with software engineers, product owners, and other cross-functional teams to support AI/ML initiatives.
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Writing clean, maintainable, and well-documented Python code for data processing, analysis, and model development.
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Creating visualizations and reports to communicate analytical findings and model performance to both technical and non-technical audiences.
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Monitoring model performance, validating results, and supporting continuous model improvement through experimentation and evaluation.
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Using SQL to extract, manipulate, and validate data from various data sources.
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Managing code and experiments using Git, Jupyter Notebooks, and project management tools such as Jira.
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Continuously researching new AI, machine learning, and data science techniques to improve existing solutions and support innovation.
We’ll know you can make it if you have:
•
1+ year of hands-on experience in data science, machine learning, or advanced data analytics.
•
Basic understanding of the Software Development Lifecycle (SDLC) and Agile/Scrum project frameworks.
•
Experience in the end-to-end data pipeline, including:
•
Data exploration and preprocessing (cleaning, missing value handling)
•
Feature engineering and selection
•
Model training, validation, and performance evaluation
•
Familiarity with project management and code management tools (e.g., Jira, GitHub).
•
Understanding of data science documentation and workflows:
•
Jupyter Notebooks / documentation of experiments
•
Model performance metrics and benchmarks
•
Data dictionaries and schemas
•
Ability to analyze business requirements and translate them into data-driven solutions or predictive models.
•
Strong proficiency in Python and core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
•
Solid understanding of databases and SQL basics for data extraction, manipulation, and validation.
•
Familiarity with exploratory data analysis (EDA) and data visualization tools (e.g., Matplotlib, Seaborn, Tableau, or PowerBI).
•
Basic knowledge of version control systems (specifically Git).
•
Fundamental understanding of core ML concepts (supervised vs. unsupervised learning, regression, classification, clustering).
•
Strong analytical thinking, mathematical intuition, and a high attention to detail regarding data quality.
•
Good problem-solving skills and the ability to challenge assumptions about data and model behavior.
•
Ability to work both independently and collaboratively with engineers and business stakeholders.
•
Good written and verbal communication skills in English (specifically the ability to explain technical insights to non-technical teams).
•
Proactive attitude and a strong willingness to stay updated on rapidly evolving AI/ML trends.
Nice to have:
•
Exposure to modern Generative AI techniques, Large Language Models (LLMs), or prompt engineering.
•
Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
•
Familiarity with processing large-scale datasets using cloud environments or distributed computing (e.g., basic Spark/Databricks).
•
Basic knowledge of ML deployment concepts or MLOps pipelines (e.g., tracking experiments with MLflow, Docker basics).
Our gratitude for the job done will be eternal, but we’ll also offer you:
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Innovative technologies and platforms to “play” with.
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Modern working environment for your comfort.
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Friendly, ambitious, and motivated teammates to support each other.
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Thousands of online and in-person learning opportunities to grow.
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Challenging assignments and career development opportunities in multinational environment.
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Attractive remuneration package.
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Flexible working schedule and opportunity for home office;
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Numerous additional goodies, including, but not limited to free A1 services, discounts, health insurance and services, sports center, childcare, team and family events, etc.
Not sure yet? See us in action in our A1 Blog.
Any questions? Contact Mariya Ivanova.
Sounds good? Apply now!
Only shortlisted candidates will be contacted.
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