Jobs Data Science

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.

Responsibilities: 

• Implement and optimize low-level computer vision algorithms under guidance
• Contribute to modules related to feature extraction, tracking, matching, and geometric processing
• Assist in the integration and testing of SLAM/VIO components
• Perform experiments, analyze results, and help prepare reports
• Work closely with senior engineers to explore and apply recent CV research.

Required Qualifications:

• 1+ years of hands-on experience with classical computer vision
• Basic understanding of geometric computer vision principles
• Experience implementing low-level CV algorithms (e.g., filtering, feature detection, camera models)
• Familiarity with SLAM or VIO concepts
• Working knowledge of C++ and Linux
• Ability to learn quickly and navigate recent CV researc
• Degree or ongoing studies in a STEM field.

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems

Position Overview

We are seeking an experienced Data Scientist/ML Engineer specializing in neural networks, with 3+ years experience in the applied field. The ideal candidate should be a great mentor and team player; python ninja with a strong background in various neural network architectures (recurrent, convolutional, feedforward, etc.) and a deep understanding of developing, tuning, and deploying different architectures. This role also requires excellent Python programming skills and a solid foundation in data analysis and statistics. If you strive in a fast pace environment, with tight deadlines but fast professional growth, you are welcome in our team!

Key Responsibilities:

• Create statistical summaries to support hypothesis testing and data-driven decisions during EDA
• Implement data preparation and feature engineering pipelines for the models
• Plan and implement algorithms for predictive modeling.
• Provide continuous improvement of models in production
• Lead the ML-driven python coding for end to end model deliveries, support our ML-related libraries/
• Collaborate with a cross-functional team of specialists, including senior and junior data scientists, Python developers and ML engineers, data analysts, and DevOps specialists.
• Provide expertise in tuning loss functions, metrics, sample weights adjustment, hyperparameter tuning and model improvement in general.
• Generate detailed evaluation reports, summarizing key findings and presenting actionable insights to stakeholders.
• Keep up with tight deadlines, agile environment of work with evolving objectives and KPIs, having the highest level of organisation and self management to provide a full work clarity, extensive tracking and documentation of your work.

Required Skills and Qualifications:

• Minimum of 3 years of professional experience as a Data Scientist or Machine Learning Engineer.
• Proficient in building custom neural networks using PyTorch.
• Strong experience with various neural network architectures specialised for time-series modelling and tabular data predictive modelling 
• Proficiency with neural network layers (like LSTM, GRU, Conv1D, Dense, Dropout, BatchNormalization) and activation functions (ReLU, Sigmoid, Tanh, Softmax).
• Experience with time series data, including loading, cleaning, and feature engineering using libraries like pandas, numpy. Knowledge of Darts library would be a large bonus.
• Expertise in model development, including selecting and developing models from the Darts library and building custom neural network architectures.
• In-depth knowledge of Python programming and relevant libraries (e.g., Scikit-learn, Pandas, PyTorch, Shap). We want to emphasize this requirement of excellency in python, including good working OOP knowledge. We do noе accept candidates with partial experience in python, as our projects require solid programming skills for writing and supporting data science related functionalities and libraries
• Solid understanding of statistics and data analysis.
• Skilled in using and tuning loss functions such as MSE, MAE, Cross-Entropy Loss, and custom loss functions relevant to time series forecasting.
• Experience with hyperparameter optimization using libraries like Optuna or Hyperopt.
• Capable of implementing and optimizing training loops in PyTorch, including data loaders and training validation steps.
• Knowledge of time series-specific cross-validation techniques and regularization methods to prevent overfitting.
• Strong skills in evaluating model performance using metrics like MSE, RMSE, MAE, MAPE, and R-squared.
• Familiarity with backtesting functionalities for validating model performance.
• Experience in model deployment, including serialization and deployment of models for real-time services.
• Strong communication skills for presenting findings and progress to stakeholders, using visualizations created with matplotlib, seaborn, or plotly.
• Proficiency in using Git for version control and collaboration.
• Major education in Data Science, Computer Science, or a related field IS A MUST. We do not accept people with other backgrounds.
• Certifications in deep learning are preferred.
• Excellent command of spoken and written English.
• Strong self-management, time management, and organizational skills.

• Ability to work under a structured management system while independently handling creative tasks.

   

What We Offer:

• Competitive remuneration package.
• Bonuses
• Professional mentorship and guidance from experienced team members.
• Opportunities for professional growth and continuous learning.
• A dynamic and collaborative work environment.
   

About DataObrii
DataObrii is a high-tech consulting firm specializing in data science, machine learning, and AI-augmented Internet of Things. Our team comprises experienced data scientists, python engineers, devops, hardware electrical engineers, and business analysts dedicated to delivering innovative, data-driven solutions that enhance business intelligence and efficiency. We emphasize continuous improvement, keeping up with current and emerging technologies, and delivering complete timely, effective solutions.

Our Values:

• Efficiency: We employ an agile approach to ensure timely delivery of high-quality solutions. This governs fast delivery cycles, quick and efficient solutions, iteratively going from PoC developments to fully enhanced production systems.
• Professionalism: Our commitment to excellence drives us to achieve success for our clients. This includes both technical and ethical proficiency required from all our employees.
• Creativity: We utilize design thinking to develop innovative solutions that address complex business challenges.
• Care: We invest time in understanding our clients' business models to provide tailored solutions that align with their objectives.
   

About The Role

As a Senior/Lead Software Engineer in our Machine Learning department, you will take ownership of high-impact initiatives that drive product quality, monetization, and user experience. You’ll apply your expertise in Python, data analysis, and modern AI tools to build, deploy, and optimize ML solutions end-to-end. This is a hands-on technical role that blends data science and engineering to deliver measurable business outcomes. You’ll collaborate closely with cross-functional stakeholders and contribute to evolving areas such as LLMs, Generative AI, and ML infrastructure. The role offers exposure to complex data challenges and the opportunity to shape Pearl’s AI-driven capabilities.

What You’ll Do

• Build, train, and deploy ML models that improve product performance and monetization.
• Collaborate with data, product, and engineering teams across multiple internal initiatives.
• Design and implement data pipelines for extraction, transformation, and analysis.
• Apply statistical and machine learning techniques to real-world business problems.
• Work on projects involving LLMs and Generative AI technologies.
• Analyze large datasets to identify trends, insights, and optimization opportunities.
• Integrate ML models into production systems and monitor their performance.
• Communicate findings and recommendations clearly to technical and non-technical stakeholders.
• Experiment with emerging AI tools and methodologies to enhance existing workflows.
• Ensure data quality, reliability, and scalability in all deliverables.

What We’re Looking For

• 3+ years of hands-on experience in ML Engineering or Data Science.
• 5-6+ years total experience in software or data engineering.
• Strong programming skills in Python.
• Proficiency in SQL for data querying and analysis.
• Solid understanding of data processing, analysis, and visualization.
• Experience with LLMs / Generative AI tools (e.g., OpenAI, Copilot, Cursor).
• Ability to build and deploy ML models end-to-end.
• Strong analytical and problem-solving mindset.
• Experience with .NET for integration work
• Upper-intermediate English proficiency (B2 or higher).
• Familiarity with Databricks or similar data platforms (nice-to-have).
• Exposure to AWS or other cloud-based ML environments (nice-to-have).

Why Join Us?

• High-Impact Data — Work with vast datasets generated by over a million daily visits, uncovering valuable insights.
• Collaborative Analytics Team — Join a team of 30+ skilled analysts who actively share knowledge and support each other.
• Cutting-Edge Tools & Techniques — Get hands-on experience with ML, Bayesian methods, and LLMs to solve real business challenges.
• Data-Driven Culture — Thrive in an environment where data informs every decision and drives continuous improvement.

Requirements: 
Address data is a central component of many processes within Westnetz. It is required for numerous applications, such as the installation of electricity meters, the connection of gas pipes, the billing of services or the deployment of technicians in the field.
Different types of address data are required depending on the use case. As part of a centrally managed expansion project, the address data system to be used by Westnetz for all central IT systems in future is to be fundamentally expanded. The main objective is to expand the address data repository with an additional address data pool in order to supply the required address data to the consuming systems.
In addition, enhancements will be implemented to make the system more user-friendly.

As part of the expansion of an address data master, the following services are to be provided:
- Performing the matching of various address data pools (geodata and attribute data) by developing a matching algorithm with adjustable thresholds
- Carrying out test management: creating test cases, executing the test cases, documenting the test results
- Documenting the interface tests
- Carrying out address data analyses and processing on Azure in SQL, Python and Spark to determine the quality of the address data

Profile:
- A degree in Computer Science, Business Informatics, Industrial Engineering or a related field
- Professional experience as a Data Scientist or in a similar role
- In-depth knowledge of Python, SQL and Spark
- Analytical thinking, structured approach to work

 

Experience in fraud detection (highly preferred) + ability to independently scope and lead ML project end-to-end

Requirements

Position name: Senior Data Scientist — Anti-Fraud System

Level: Senior / Middle+

Hard skills requirements (including years):

• Strong experience in Data Science / Machine Learning
• Experience in fraud detection systems — highly preferred
• Ability to transition rule-based systems to ML/predictive models
• Experience with near real-time data processing
• Strong knowledge of statistical modeling and ML algorithms
• Python (preferred stack, final decision left to the DS)
• SQL and database proficiency
• Ability to independently scope a data environment and define technical approach

Soft skills requirements:

• Ability to independently lead a project end-to-end
• Strong communication skills (stakeholder alignment required)
• Self-driven, proactive, consultative mindset

Office/Remote: Remote

Project tasks:

• Scope existing rule-based fraud detection system (16 static flag types) and define technical approach
• Propose and implement ML stack and architecture
• Evolve system into dynamic, predictive, learning-based fraud detection model
• Work toward near real-time fraud processing as the project scales
• Work as part of 2-person AI team with full ownership of the anti-fraud project
• Facilitate stakeholder alignment

English level: Upper-Intermediate

As a Machine Learning Engineer, you'll work as part of the Wix CTO Office team, researching problems that can give Wix’s products a competitive edge across various challenges. A key focus of the team is on Agents over LLMs, exploring new techniques for building agents and developing innovative products that leverage them.  

In your day-to-day, you will:  

• Build POCs for research projects led by the team  
• Evaluate results and provide actionable insights  
• Collaborate with different teams at Wix to advance their agent implementations  

• Build shared infrastructure for agents  

   

Requirements

• 5+ years building and maintaining production-grade systems at scale
• Proficient in TypeScript; Java and/or Python is a significant advantage
• Hands-on experience building GenAI systems with LLMs and agents
• Deep expertise in at least 2 of: Agentic Orchestration & Tool-Calling, Advanced RAG, Automated Evaluation & Testing
• BSc in Computer Science or related field; MSc preferred
• Excellent communication skills in English; collaborative and comfortable with ambitious, high-risk problems

About the Team  

We are Wix's Data Science CTO Office team, a small group of researchers and engineers. We collaborate with various groups at Wix and the CEO on innovative research projects. Some projects aim to enhance Wix products with new features, while others focus on strategic research areas that can provide Wix with a competitive advantage.

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.

We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

Our client is looking for a Data Science / AI Engineer to help build an autonomous platform that turns product requirements into production-grade code.

The product leverages AI to automate development workflows and dramatically increase R&D productivity. Already in production with active customers, the team is now scaling both the technology and impact.

Key Requirements:
🔹 7+ Years Experience: Deep professional background in AI/Data Science;
🔹 Agent Expert: Proven experience building high-quality agentic systems—specifically dealing with planning, tool-calling, and self-correction loops;
🔹 Sophisticated Retrieval: Expertise in building retrieval systems that can deal with real, complex cases (not just basic vector search);
🔹 Technical Excellence: Expert-level Python. You must be able to contribute to a production-grade backend and bridge the gap between a model's output and a functional tool;
🔹 AI Native: Power user of Claude and Cursor;
🔹 Advantage: Hands-on experience with LLM Evaluation suites and moving agentic systems from "cool demo" to "production reliable.";
🔹 Production Focus: Experience delivering solutions that are robust, reliable, and maintainable in real-world, customer-facing environments;
🔹 Database Skills: Experience with indexing, vector databases, and data retrieval at scale;

What you will do:
🔹 Planning & Reasoning: Design and optimize multi-step planning systems that allow agents to decompose high-level requirements into executable, low-error technical strategies;
🔹 Agentic Retrieval: Architect retrieval systems (GraphRAG, hybrid search) that can handle real-world codebase complexity, ensuring agents retrieve the right context for the right task;
🔹 Evaluation & Evals: Build robust, automated evaluation frameworks to measure agent success and reliability. You'll define what "high-quality execution" looks like in a machine-readable way;
🔹 Performance Optimization: Use few-shot learning, prompt engineering, and targeted fine-tuning to make agentic workflows deterministic and reliable in production;
🔹 From Demo to Production: Move beyond "agent-in-a-box" prototypes. You are responsible for the stability and quality of agents performing end-to-end SDLC tasks;
🔹 Customer Impact: Work closely with product and engineering teams to understand customer needs, solve real-world problems, and deliver solutions that move the needle for customers;
🔹 End-to-End Ownership: Take responsibility for projects from research and prototyping through to production deployment and ongoing optimization;
🔹 Product Mindset: Bring a product-oriented approach, proposing improvements and new features that align with business goals and customer requirements;
🔹 Collaboration: Communicate effectively with cross-functional teams and, when needed, with customers to gather feedback and ensure solutions meet real-world needs;
🔹 Proactive Problem Solving: Identify and address bottlenecks or new opportunities in agentic workflows and retrieval systems;

Interview stages:
🔹 HR Interview;
🔹 Technical Discussion ;
🔹 Practical Session ;
🔹 Team Fit Conversation ;
🔹 Final Review;
🔹 Reference Check;
🔹 Offer;

Why Join Us?

At YozmaTech, we’re self-starters who grow together. Every day, we tackle real challenges for real products – and have fun doing it. We work globally, think entrepreneurially, and support each other like family. We invest in your growth and care about your voice. With us, you’ll always know what you’re working on and why it matters.
From day one, you’ll get:
🔹 Direct access to clients and meaningful products;
🔹 Flexibility to work remotely or from our offices;
🔹 A-team colleagues and a zero-bureaucracy culture;
🔹 Opportunities to grow, lead, and make your mark.

After you apply

We’ll keep it respectful, clear, and personal from start to offer.
You’ll always know what project you’re joining – and how you can grow with us.

Everyone’s welcome

Diversity makes us better. We create a space where you can thrive as you are.

Ready to build something meaningful?

Let’s talk. Your next big adventure might just start here.

Domain: iGaming / Gambling
Format: Product company
Experience: 5+ years

About the Company

We are an international product company operating in the gambling sector. Our platform delivers real-time personalization for casino and sportsbook products using advanced machine learning. The solution processes live behavioral, transactional, and contextual data to improve player engagement, retention, and overall performance for operators worldwide.

Our focus is on building production-grade ML systems that directly influence what users see in real time — from game recommendations to personalized content and promotions.

Role Overview

We are looking for a Senior Data Scientist to join a product-focused team working on real-time personalization and recommendation systems for iGaming platforms.

This is a hands-on role that combines modeling, experimentation, and close collaboration with engineering and product teams in a high-load, real-time production environment.

Main Responsibilities

• Develop ML-driven features for casino products using supervised learning (regression, ranking, classification)
• Maintain and improve existing recommendation systems in production
• Enhance models using gradient boosting and other supervised approaches
• Perform data cleaning, preprocessing, and feature engineering
• Design and maintain pre- and post-processing workflows
• Optimize training and inference pipelines for performance and reliability
• Integrate ML models into Airflow pipelines in a multi-tenant environment
• Adapt and configure the solution for different clients (tenants)
• Collaborate closely with product and engineering teams on experimentation and feature delivery

As Part of the Team You Will

• Work cross-functionally with data scientists, engineers, product owners, designers, and researchers
• Analyze large-scale datasets to extract insights for product and business decisions
• Propose, implement, and evaluate ML approaches to solve real business problems
• Support and evolve a recommendation solution used across multiple tenants
• Influence product strategy through research, experimentation, and data-driven insights into user behavior

Experience & Education

• 5+ years of professional experience in data science
• Degree in a quantitative field (Mathematics, Statistics, Computer Science, or similar)

Core Skills

• Strong proficiency in Python and SQL
• Hands-on experience with data processing tools (Pandas, Polars)
• Solid engineering skills for building and maintaining scalable ML systems
• Experience implementing observability in ML pipelines (metrics, logging, alerting)
• Knowledge of Docker and Kubernetes
• Strong analytical mindset with the ability to solve loosely defined problems
• Hands-on experience with supervised ML techniques, including:
  • Regression and ranking models (XGBoost, LightGBM, CatBoost, neural networks)
  • Feature engineering and model evaluation (AUC, NDCG, MSE, uplift metrics)
  • Personalization or recommendation systems
• Proven experience deploying ML models to production (near real-time or batch)
• Solid understanding of statistical methods (A/B testing, significance testing)

Nice to Have

• Production experience with large-scale recommendation systems
• Experience with Airflow, Valkey/Redis, FastAPI in production
• Familiarity with contextual bandits or reinforcement learning
• Experience with AutoML tools

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

We deliver an AI-driven video platform that automatically identifies and extracts the most engaging segments from live and on-demand video feeds, generates dynamic teasers and summaries, indexes content for rapid retrieval, and transforms formats (e.g., horizontal to vertical). Our solution serves global media, sports, news, and gaming organizations, processing petabytes of visual data and supporting millions of end users.

Engineers face challenges in computer vision research, big data analytics, and production-grade cloud infrastructure to enable near-real-time processing, seamless scaling, and high-throughput delivery.

About the Role:

As a Senior Algorithms Engineer, you will bridge cutting-edge research and production systems, owning design, implementation, and scaling of advanced computer vision and AI models.

You will invent new approaches using deep learning, large language models (LLMs), and vision-language models (VLMs) and lead end-to-end engineering from prototype to cloud deployment.

Key Responsibilities:

• Design, prototype, and validate computer vision and ML algorithms using PyTorch, TensorFlow, OpenCV and LLM/VLM APIs.
• Analyze multi-terabyte video datasets to identify patterns, perform behavioral analytics, and build predictive models.
• Develop and maintain an Algo-Ops framework for seamless integration, monitoring, debugging, and scaling of algorithms in cloud environments.
• Work closely with DevOps to deploy and scale models in production (no need to own infrastructure).
• Evaluate and integrate emerging video-language and generative AI models (e.g., Gemini, open-source VLMs) into processing pipelines.
• Collaborate with cross-functional teams to translate research prototypes into production-grade features and participate in on-call support when needed.
• Continuously research and adopt new AI tools (Claude Code, Cursor, etc.) to enhance workflows and iterate on model performance.

Required Competence and Skills:

• At least 8 years of professional software development experience. 
• 4+ years of Python experience.
• Expert-level hands-on proficiency with PyTorch and TensorFlow.
• Experience with video processing and computer vision libraries.
• Solid understanding of cloud infrastructure and DevOps basics (AWS, GCP, Bash, Nomad).
• Hands-on experience using AI tools (LLMs/VLMs, agentic workflows).
• Proven ability to analyze large-scale datasets and implement predictive behavioral models.
• Self-starter with strong autonomy to research, lead, and execute complex technical projects end-to-end.
• M.Sc. or higher in Computer Science, Electrical Engineering or equivalent.

Nice to Have:

• Experience integrating models like GPT, Gemini, or open-source VLMs
• Proficiency with big data tools (Spark, Iceberg, PostgreSQL, Elasticsearch, Redis).
• Working knowledge of containerization and orchestration platforms (Docker, Kubernetes, Nomad).

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.

About Us:

Evowill is looking for a Junior Data Scientist who is passionate about data analysis, machine learning, and extracting insights from data, and eager to grow in a supportive and dynamic environment. We offer a clear path: starting with a hands-on internship and transitioning into a commercial project role — 100% of our juniors join real projects.

Requirements:

• Knowledge of Python
• SQL (MySQL / PostgreSQL)
• Basic understanding of Machine Learning (scikit-learn)
• Basic data analysis skills (Pandas, NumPy)
• Solid statistics foundations
• Git, GitHub/GitLab
• English: Intermediate
• Pet projects (data analysis / ML) 
• Fast learner, organized, responsible
  
   

Would be a plus:

• Quantitative Science (Math, physics, statistics) or Engineering with ML or modeling majors (3rd year or higher)
• Experience with statistical or numerical modeling or having participated in data related research teams
  
   

Internship Stage (2 months):

• Full-time, practical learning
• Pet projects, technical interview preparations, and soft skills training
• English Speaking Club
• Senior Developers mentors from Ukraine and Colombia
• Technologies: Core Data Analysis and Modeling, Python libraries, as well as learning to apply modern ML techniques to real-world data.

Project Stage:

• Join commercial projects as a Data Scientist
• Salary from $1000 with regular reviews
• Ongoing mentorship and technical support
• Optional English club and extra tech learning

Progresstech Ukraine is seeking for MATLAB Simulink Engineer. The primary responsibility in this role will be addressing development of airplane systems as well as creative generation of computer models of airplane systems for future airplane design, test, and analysis endeavors.

There are some general directions of our project to support the latest functional systems for Boeing aircrafts:

• Develop, maintain, update, and integrate code using MATLAB Simulink and/or C/C++ representing the mathematical and physics behavior of airplane engineering systems
• Integrate complex software components into fully functional systems
• Develop software verification plans, test procedures and test environments, execute the test procedures and documents test results to ensure software system requirements are met
• Analysis of flight data, data verifying

Basic Qualification:

• At least a bachelor's degree in engineering, computer science, mathematics, physics, etc.
• MATLAB Simulink experience
• Project documentation skills

Preferred Qualification:

• Ability to understand complex airplane systems design, functionality, and architecture
• Non-Software Engineer with the ability to understand/use/learn software languages and development tools
• C/C++ programming experience
• Knowledge of ARINC coding rules
• Technical writing

Project description

As part of the AI transformation strategy, Kyivstar invests resources in the integration of GenAI/Speech technologies into internal processes and day-to-day tasks, but also uses gained experience to help partners and clients to receive maximum benefits from these technologies too.

One of the key directions of this strategy is the development of AI assistants and services for external partners and clients. To achieve this, company is looking for AI Engineer (Speech) - specialists in the field of GenAI and Speech Processing with deep ML/DL background and practical skills in developing AI assistants and voice bots.

Necessary skills

• 4+ years of experience in ML/DL with strong focus on STT/TTS
• Hands-on experience training and deploying models for various speech processing tasks (e.g., speech classification, speech-to-text, text-to-speech, and speaker diarization)
• Practical experience building AI applications using LLMs
• Strong Python skills with experience in writing scalable software modules
• Fundamental knowledge of  ML/DL theoretical concepts
• Familiarity with RESTful APIs and basic web development principles
• Proficient in version control (Git) and containerization tools (Docker)

Would be a plus

• Experience with real-time / low-latency speech systems
• Experience with distributed data processing and training in multi-node, multi-GPU environments
• Experience with LangChain, LangGraph, and FastAPI
• Experience with Azure/AWS
• Familiarity with PySpark for large-scale data processing
• Exposure to Data Science in the Telecom industry

Responsibilities

• Design, train, and optimize ASR and TTS models for production use
• Design and develop AI-powered assistants
• Fine-tune and optimize large-scale models for specific business needs
• Collaborate with DevOps team to deploy the solution

• Plan and manage ML projects, articulate methodologies, and communicate results and business impact to stakeholders and customers

   

Proposed:

• Working with huge amounts of data at the largest operator in Ukraine
• Hands on experience with Cloud technologies and tools
• Great diversity of tasks and projects to utilize your knowledge and skills; flexibility in tools and approaches
• Opportunity to grow within the team of talented data scientists

We are looking for a Computer Vision Engineer with a solid foundation in classical computer vision and hands-on experience implementing low-level CV algorithms. The ideal candidate will have exposure to SLAM, Visual-Inertial Odometry (VIO), and sensor fusion, with responsibilities adjusted according to experience level.

Responsibilities: 

• Design, implement, and optimize classical CV algorithms independently
• Develop and maintain components of SLAM/VIO pipelines
• Contribute to sensor fusion modules involving visual and inertial data
• Lead experiments, evaluate model performance, and propose improvements
• Review research papers and translate findings into practical solutions
• Collaborate across teams to ensure smooth integration of CV components.

Required Qualifications:

• Strong practical experience with classical CV and geometric vision
• Hands-on experience developing components of SLAM and/or VIO systems
• Proficiency in C++ and confident working in Linux environments
• Solid understanding of multi-sensor systems and data fusion
• Proven ability to prototype, benchmark, and optimize CV algorithms
• Ability to analyze research papers and implement state-of-the-art methods.

Nice to Have:

• Experience with Python
• Knowledge of neural networks and CV libraries/frameworks (OpenCV, NumPy, PyTorch, ONNX, Eigen, etc.)
• Experience with sensor fusion techniques
• Familiarity with embedded or real-time systems

Almus is looking for a Data Scientist to join our Analytics team and build production-grade machine learning models that directly impact marketing and business performance.

You will work on end-to-end ML solutions, from data and features to deployment and monitoring, focusing on improving LTV prediction quality, optimizing ML-driven costs, and driving key metrics such as LTV, ROAS, retention, and CAC. This is an individual contributor role with strong ownership, close collaboration with Marketing, Product, and Data teams, and a clear focus on real business impact.

Apply to join Almus and take ownership of high-impact data initiatives!

Responsibilities

• Design, develop, and deploy machine learning models to production
• Improve product and business decision-making through data-driven approaches
• Build and evolve end-to-end ML pipelines (data → features → model → inference → monitoring)
• Drive measurable impact on key product and commercial metrics
• Standardize ML approaches within the team (best practices, documentation, reproducibility)
• Provide technical input to the architecture of analytics and ML infrastructure
• Develop and deploy models that drive growth in LTV, ROAS, retention, and CAC
• Influence performance and lifecycle marketing strategy
• Act as a domain expert and collaborate closely with Marketing, Product, and Data Engineering teams

What We Look For

• 3+ years of experience as a Data Scientist / ML Engineer
• Experience working with mobile subscription-based products
• Strong Python skills (production-level code)
• Solid knowledge of classical machine learning algorithms and practical experience applying them
• Experience with feature engineering, model evaluation, and bias–variance trade-offs
• Hands-on experience with marketing models such as LTV, churn, cohort, and funnel modeling
• Experience with attribution, incrementality, and uplift modeling
• Strong SQL skills and experience working with analytical datasets
• Experience with production ML systems and A/B testing

• English level: Intermediate+

   

Nice to have

• Experience with BigQuery
• MLOps experience (Docker, CI/CD, model registres)
• Experience working with performance marketing data (Meta, Google Ads, Adjust)
• Knowledge of causal inference

• Experience with AutoML and Bayesian models

   

We Offer

• Exciting challenges and growth prospects together with an international company
• High decision-making speed and diverse projects
• Flexibility in approaches, no processes for the sake of processes
• Effective and friendly communication at any level
• Highly competitive compensation package that recognizes your expertise and experience, Performance Review practice to exchange feedback and discuss terms of cooperation
• Flexible schedule, opportunity to work in a stylish and comfortable office or remotely
• Respect for work-life balance (holidays, sick days - of course)
• Bright corporate events and gifts for employees
• Additional medical insurance
• Compensation for specialized training and conference attendance
• Restaurant lunches at the company's expense for those working in the office, endless supplies of delicious food all year round
   

ПРО ПОЗИЦІЮ

Вимоги:

• Досвід DS/MLE від 2 років
• Математичний бекграунд: вища математична освіта (КПІ ІПСА, МехМат Шевченко тощо), бажано олімпіадний досвід
• Глибокі знання алгоритмів і структур даних, глибоке розуміння ООП, глибокі теоретичні та практичні знання машинного та глибокого навчання
• Практичний досвід вирішення NLP та Tabular Data ML задач
• Високий рівень володіння Python, включаючи досвід роботи з бібліотеками машинного навчання і володіння принаймні одним із фреймворків глибокого навчання (Tensorflow, Keras, PyTorch)
• Вміння писати чистий, підтримуваний та ефективний код, готовий до production
• Вміння трансформувати бізнес-вимоги у технічні завдання для ML-рішень
• Досвід feature engineering
• Досвід роботи з Git та Docker
• Досвід роботи з базами даних (SQL/NoSQL) для отримання та підготовки даних для моделей

Буде плюсом:

• Досвід вирішення CV завдань
• Досвід успішних виступів на хакатонах/Kaggle
• Досвід роботи з Airflow на рівні запуску та моніторингу завдань
• Розуміння принципів паралелізму в Python та досвід роботи з відповідними бібліотеками

Приклади задач:

• Підвищення точності поточних CV, NLP та інших моделей
• Розробка нових моделей з нуля: від R&D та feature engineering до валідації
• Аналіз великих обсягів даних для пошуку інсайтів та формулювання гіпотез для моделювання