Jobs

In Competera, we are building a place where optimal pricing decisions can be made easily. We believe that AI technologies will soon drive all challenging decisions and are capable of helping humans be better. We are now looking for a Middle Data Scientist to change the way we deliver our solution to customers.
 

You could be a perfect match for the position if

You want to:

• Validate datasets to ensure data accuracy and consistency.
• Design proof-of-concept (POC) solutions to explore new approaches.
• Develop technical solutions by mapping requirements to existing tools and functionalities.
• Train models and create custom approaches for new domains.
• Troubleshoot data processing and model performance issues.

You have:

• 2+ years of experience in data science or a related field.
• Strong SQL skills for data manipulation and extraction.
• Proficiency in Python, with the ability to write modular and readable code for experiments and prototypes.
• A solid mathematical background, preferably in a Computer Science-related field.
• Expertise in scientific Python libraries, including NumPy, pandas, scikit-learn, and either Keras/TensorFlow or PyTorch.
• Familiarity with Time Series Forecasting methodologies.
• Experience in statistical testing, including A/B testing.
• 1+ years working with tabular and multimodal data (e.g., combining tabular data with text, audio, or images).
• Upper-intermediate or higher English level.

Soft skills:

• Analytical mindset and critical thinking to solve complex problems.
• Agile approach, with the ability to experiment and test hypotheses in a dynamic business environment.
• Business-oriented thinking, capable of translating complex models into clear business insights.
• Curiosity and a drive for continuous learning in the data domain.
• Strong team player, able to collaborate across cross-functional teams.

You’re gonna love it, and here’s why:

• Rich innovative software stack, freedom to choose the best suitable technologies.
• Remote-first ideology: freedom to operate from the home office or any suitable coworking.
• Flexible working hours (we start from 8 to 11 am) and no time tracking systems on.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• Competera covers 70% of your training/course fee.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• Partial medical insurance coverage.
• We reimburse the cost of coworking.

Drive innovations with us. Be a Competerian.

We’re looking for a proactive Data Scientist to join our growing team and help us redefine the future of eSports betting! You will develop and implement advanced models for esports betting, focusing on games such as Dota 2, League of Legends, etc. Oversee the entire model development lifecycle, including design, testing, and performance optimization.

Are you ready to apply your expertise in a fast-paced, innovative environment? If you’re passionate about quality and love the idea of working on a cutting-edge product, keep on reading!

Who are we?
 

Since 2017, our team of tech enthusiasts, eSports players, and bettors has been on a mission to revolutionize the world of eSports betting. This passion has driven us to create DATA.BET, the fastest-growing eSports data product in the market.

With the widest event coverage and a turnkey solution for a full betting product, we aim to become the TOP provider in the industry.
 

What you’ll be working on:
 

• Develop and implement betting models using Python and Golang.
• Design and optimize mathematical models, including statistical models, classical machine learning techniques, and neural networks.
• Analyze the performance and impact of models, ensuring operational efficiency.
• Prototype and assess models to evaluate their effectiveness and user acceptance.
• Integrate models with existing systems and optimize performance.
• Collaborate with backend and frontend teams for seamless implementation and decision-making.
• Conduct in-depth statistical analysis and apply machine learning methods to enhance forecasting accuracy.
   

About you:

We’re looking for someone who thrives on precision and collaboration.

Must-have skills and experience:
 

• 3+ years of commercial experience with Python.
• Strong knowledge of statistics and practical experience with ML techniques.
• Proven expertise in mathematical modeling, including statistical methods, classical ML approaches, and neural networks.
• Strong data processing skills (validation, parsing, visualization).
• Understanding business logic of decisions and analytical thinking ability.
• Excellent communication skills and the ability to work in a team.
• Ability to assess the business value of tasks.
• Upper-intermediate English skills.
   

Nice to have:
 

• Higher education in computer science, mathematics, statistics, or a related discipline is a plus.
• Experience in the betting industry or related fields is an advantage.
   

Why work with us?
 

We offer not just a job but an opportunity to be part of an innovative, and ambitious team that cultivates a positively charged atmosphere and an environment that fosters both professional and individual growth.

Your well-being and a supportive work environment are our biggest priority:
 

• Flexible schedule and workplace options: enjoy the flexibility to work where and when you’re most productive.
• 20 Paid+15 unpaid vacations: take time off to recharge with both paid and unpaid vacation options.
• Day off for your birthday: celebrate your special day with a well-deserved day off.
• Health insurance: take care of yourself and your well-being with comprehensive health coverage (in Ukraine only).
• 22 Sick leaves: take enough time to recover with a sufficient sick leave allowance (12 unconfirmed including sick leaves for mental health + 10 confirmed)
• Gifts and bonuses (wedding, child birth bonus, kindergarten allowance (in Ukraine only): get special perks to support you in various life situations and important moments.

Fozzy Group is one of the largest trade industrial groups in Ukraine and one of the leading Ukrainian retailers, with over 700 outlets all around the country. It is also engaged in e-commerce, food processing & production, agricultural business, parcel delivery, logistics and banking. 

Since its inception in 1997, Fozzy Group has focused on making innovative business improvements, creating new opportunities for the market and further developing the industry as a whole.

At Fozzy Group, we are developing a next-generation Decision Support System to manage assortment and promotional activities more effectively using advanced analytics and machine learning. The project focuses on two major streams:

• Assortment Optimization: Cluster-based assortment planning, product lifecycle management, and inventory rotation strategies.
• Promo Effectiveness & Forecasting: ML-driven analysis and prediction of promo impact, segmentation-based targeting, and ROI estimation.

You will join a cross-functional team to design and implement data-driven decision module that directly influence commercial and operational decisions.

Job Responsibilities:

• building ML models for low-rotation SKU detection, promo TS models, and assortment clustering;
• supporting planogram and replenishment logic development with data-driven insights;
• automating recommendations for promo selections and substitutions;
• Design, train, and validate predictive and prescriptive models for promo uplift, inventory turns, and customer response;
• build and maintain SQL pipelines to aggregate and transform commercial data from various sources;
• collaborate with category managers, marketing, supply chain, and IT to translate business goals into measurable analytics tasks.

Requirements:

• bachelor’s Degree in Mathematics / Quantitative Economics / Econometrics / Statistics / Computer Sciences / Finance;
• at least 2 years working experience on Data Science;
• strong mathematical background in Linear algebra, Probability, Statistics & Optimization Techniques;
• proven experience with SQL (Window functions, CTEs, joins) and Python;
• machine Learning techniques (e.g., Decision Trees, Random Forest, and Boosting), Time Series Analysis and application of Statistical Concepts (Hypothesis testing, A/B tests, PCA);
• ability to work independently and decompose complex problems.

Preferred:

• knowledge of Reporting and Business Intelligence Software (Power BI, Tableau, Looker);
• experience with Airflow, Docker, or Kubernetes for data orchestration;
• practical experience with Amazon SageMaker: training, deploying, and monitoring ML models in a production environment;
• ability to design and deliver packaged analytical/ML solutions.

By joining our team you will get:

• opportunity to generate and influence decisions;
• competitive salary;
• professional & personal development opportunities;
• being part of dynamic team of young & ambitious professionals;
• concierge service for employees;
• corporate discounts for sport clubs and language courses;
• paid vacation and health insurance.

МІЙ БАНК — МОЯ ОПОРА.

Опора мільйонів українців, хто відтепер каже «МОЄ».

МОЇ ЛЮДИ. МОЯ СПРАВА. МОЯ СВОБОДА.

ОЩАДБАНК запрошує до команди Middle Data Scientist

Ключові завдання:

• Розробка та впровадження моделей прогнозування (класифікація, регресія) для фінансових даних.
• Оптимізація та налаштування tree-based моделей (XGBoost, LightGBM) для покращення їх ефективності.
• Проведення глибокого аналізу даних та feature engineering для підвищення якості моделей.
• Співпраця з інженерами даних для створення ефективних пайплайнів машинного навчання.
• Розробка та впровадження систем моніторингу продуктивності моделей.

Для даної посади необхідні:

• 2+ років досвіду в Data Science.
• Досвід створення та впровадження прогнозних моделей на табличних даних.
• Вища освіта в галузі математики, комп’ютерних наук, фізики або інженерії.
• Досвід роботи з великими наборами табличних даних.

Технічні вимоги:

• Розуміння алгоритмів машинного навчання та їх застосування на табличних даних.
• Middle рівень роботи з tree-based моделями (XGBoost, LightGBM, CatBoost etc.).
• Досвід оптимізації гіперпараметрів та cross-validation технік, вимірювання впевненості моделі у своїх прогнозах (довірчі інтервали, прогнозні сети).
• Знання методів feature selection та feature engineering для табличних даних та часових рядів.
• Досвід роботи з незбалансованими датасетами (without over/down sampling techniques, other methods).
• Експертне володіння Python та його ML бібліотеками (scikit-learn, SciPy, statsmodels etc.).
• Досвід роботи з системами версіонування моделей (MLflow, DVC).
• Знання практик тестування та дебаггінгу ML моделей.