Jobs Data Scientist

About Tie

Tie is building the next generation of identity resolution and marketing intelligence. Our platform connects hundreds of millions of consumers across devices, browsers, and channels—without relying on cookies—to power higher deliverability, smarter targeting, and measurable revenue lift for modern marketing teams.

At Tie, AI is not a feature—it is a core execution advantage. We operate large-scale identity graphs, real-time scoring systems, and production ML pipelines that directly impact revenue, deliverability, and customer growth.

The Role

We are looking for a Senior AI / Machine Learning Engineer to design, build, and deploy production ML systems that sit at the heart of our identity graph and scoring platform. You will work at the intersection of machine learning, graph data, and real-time systems, owning models end to end—from feature engineering and training through deployment, monitoring, and iteration.

This role is highly hands-on and impact-driven. You will help define Tie’s ML architecture, ship models that operate at sub-second latency, and partner closely with platform engineering to ensure our AI systems scale reliably.

What You’ll Do

• Design and deploy production-grade ML models for identity resolution, propensity scoring, deliverability, and personalization
• Build and maintain feature pipelines across batch and real-time systems (BigQuery, streaming events, graph-derived features)
• Develop and optimize classification models (e.g., XGBoost, logistic regression) with strong handling of class imbalance and noisy labels
• Integrate ML models directly with graph databases to support real-time inference and identity scoring
• Own model lifecycle concerns: evaluation, monitoring, drift detection, retraining, and performance reporting
• Partner with engineering to expose models via low-latency APIs and scalable services
• Contribute to GPU-accelerated and large-scale data processing efforts as we push graph computation from hours to minutes
• Help shape ML best practices, tooling, and standards across the team

What You’ll Bring

Required Qualifications

• 5+ years of experience building and deploying machine learning systems in production
• Strong proficiency in Python for ML, data processing, and model serving
• Hands-on experience with feature engineering, model training, and evaluation for real-world datasets
• Ability to travel outside of Ukraine is a must
• Experience deploying ML models via APIs or services (e.g., FastAPI, containers, Kubernetes)
• Solid understanding of data modeling, SQL, and analytical workflows
• Experience working in a cloud environment (GCP, AWS, or equivalent)
• Experience with graph data, graph databases, or graph-based ML

• Familiarity with Neo4j, Cypher, or graph algorithms (community detection, entity resolution)

  Preferred / Bonus Experience

• Experience with XGBoost, tree-based models, or similar classical ML approaches
• Exposure to real-time or streaming systems (Kafka, Pub/Sub, event-driven architectures)
• Experience with MLOps tooling and practices (CI/CD for ML, monitoring, retraining pipelines)
• GPU or large-scale data processing experience (e.g., RAPIDS, CUDA, Spark, or similar)
• Domain experience in identity resolution, marketing technology, or email deliverability

Our Technology Stack

• ML & Data: Python, Pandas, Scikit-learn, XGBoost
• Graphs: Neo4j (Enterprise, GDS)
• Cloud: Google Cloud Platform (BigQuery, Vertex AI, Cloud Run, Pub/Sub)
• Infrastructure: Docker, Kubernetes, GitHub Actions
• APIs: FastAPI, REST-based inference services

What We Offer

• Competitive compensation, including salary, equity, and performance incentives
• Opportunity to work on core AI systems that directly impact revenue and product differentiation
• High ownership and autonomy in a senior, hands-on role
• Remote-first culture with a strong engineering and data focus
• Exposure to cutting-edge problems in identity resolution, graph ML, and real-time AI systems

• Clear growth path toward Staff / Principal IC roles

  What else:

• 4 weeks of paid vacation per year (flexible scheduling)
• Unlimited sick leave — we trust your judgment and care about your health
• US Bank Holidays off (American calendar)
• Remote-first culture and flexible working hours
• Flat structure, no micromanagement, and full ownership

• Opportunity to make a real impact during a critical growth phase

  Interview Process

• Recruitment Screening Call
• Initial call with Head of Data Science & AI and CTO  (30 min) in English
• Technical deep dive Interview (1,5h)  in English

• Optional test-task (paid)

  Why Join Us?

• High-impact delivery leadership role during a critical period
• Real ownership and autonomy
• Opportunity to shape delivery across the entire engineering organization
• Exposure to SaaS, data, integrations, automation, and platform work
• Collaboration with global teams and vendors
• A strong product with real scale and momentum

Why This Role Matters

At Tie, your work will not live in notebooks or experiments—it will power production systems used by real customers at scale. You will help define how AI is embedded into the company’s core platform and play a key role in making machine learning a durable competitive advantage.

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

Join us as a Data Architect / Lead and play a key role in shaping the data foundation behind our next generation of analytics and AI solutions. In this position, you’ll define the architecture vision for our modern data ecosystem, guide a growing team of Data Engineers, and build cloud‑native platforms that unlock enterprise‑wide insights. This is a high‑impact role where you’ll work closely with business and technology leaders, influence strategic decisions, and drive the adoption of advanced analytics and Generative AI across the organization.

What You’ll Do:

Lead & Strategize

• Lead and mentor Data Engineers, fostering innovation and continuous improvement.
• Own the data architecture vision aligned with business goals.
• Partner with executives and stakeholders to turn strategic needs into scalable data solutions.

Architect & Build

• Design and optimize modern data platforms using Azure Data Lake, Databricks, SQL Server, Microsoft Fabric, and NoSQL.
• Build robust, scalable data pipelines across diverse data sources.
• Implement strong data quality, governance, and security practices.
• Support advanced analytics, machine learning, and AI-based solutions.

Enable Insights

• Build solutions that deliver accurate, timely insights for decision-makers.
• Collaborate on Power BI dashboards and executive reporting.
• Integrate Generative AI into insight-generation workflows.

Requirements:

• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 4+ years in data engineering, architecture, or analytics roles.
• Experience leading Data Engineering teams in enterprise settings will be a plus.
• Strong skills in Azure data services, Databricks, SQL, NoSQL, and Microsoft Fabric.
• Hands-on Power BI and enterprise reporting experience.
• Proven ability to build data pipelines and enforce data quality.
• Excellent communication skills, especially with executive stakeholders.
• Relevant certifications (Azure Data Engineer, Databricks, Fabric Analytics, etc.) are a plus.

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

3 seniority levels available: Middle, Senior, Lead

Who we are looking for

We’re searching for a proactive and technically skilled Data Science Engineer with hands-on experience in building and delivering ML solutions. The ideal candidate has at least 2 years of relevant experience, a strong command of Python, practical knowledge of classical ML algorithms, and experience working on the full data science lifecycle — from data preparation through to model deployment. We value analytical thinkers who can work independently, collaborate with team members, and bring innovative ideas to solve complex business problems within real-world projects.
 

Your future role

You will work as part of the AI & Data team at Deloitte, leading end-to-end data science and machine learning tasks: from problem definition and data analysis to model building, validation, and deployment in production. You’ll be responsible for extracting and preparing raw data, building and optimizing ML models, analyzing results, and presenting actionable insights. Your tasks will also include collaborating with cross-functional teams, participating in code reviews, documenting solutions, and optionally mentoring juniors or interns.
 

What we offer

• Projects with tangible business impact and modern technical stack
• Opportunities to work with advanced ML, MLOps (Docker, KubeFlow), and deep learning frameworks
• Mentorship from senior team members and knowledge-sharing culture
• Access to international expertise and best practices within Deloitte Global
• Competitive salary & comprehensive benefits package
• Internal and external professional development, trainings, and certifications

• Flexible remote/hybrid work within Ukraine

   

More information about the company, project, and interview process will be provided in the first message after you apply.
Don’t hesitate to apply — we have several great opportunities for you to join our skilled AI team :)

About the team

Our AI & Data team transforms data into actionable insights and brings intelligent ML systems into production. We embrace experimentation and knowledge sharing, leveraging modern technologies to solve real business problems for clients in diverse industries. The team values initiative, autonomy, and professional growth, offering members the chance to deepen expertise in a collaborative and supportive environment.
 

About Deloitte

Deloitte is a global leader in audit, consulting, financial advisory, risk advisory, tax, and related services. With a presence in over 150 countries, we help clients navigate complex business challenges through innovative solutions and deep industry expertise. Our commitment to excellence, integrity, and client success drives everything we do. In Ukraine, Deloitte Digital Technology Solutions (DTS) is a hub of innovation where we build AI-powered solutions for leading enterprises across Europe and beyond.
 

Join MGID as a Data Scientist and become part of a team shaping the future of AdTech!
If you thrive on analyzing data, uncovering hidden patterns, and transforming insights into powerful solutions, this is your chance. We develop cutting-edge algorithms that drive the success of CPA  campaigns by achieving target metrics, increasing conversion volume, and maximizing budget efficiency. 

What You Will Do:

• Data Analysis: Explore data to identify trends, evaluate campaign performance, and support decision-making.
• Algorithm Development: Design, implement, and optimize algorithms for CPA optimization.
• Modeling and Optimization: Build and refine predictive models to improve decisions for CPA campaigns, ensuring alignment with business objectives.
• Stakeholder Collaboration: Work closely with product/business teams to translate technical solutions into measurable business impact.
• Experimentation and Validation: Conduct and evaluate A/B tests to assess the impact of algorithm changes.
• Visualization and Reporting: Create dashboards and visualizations to track key performance indicators (KPIs) and communicate findings to stakeholders.

Who You Are:

• Proactive problem-solving attitude: ability to independently analyze data, identify hidden issues, formulate hypotheses, suggest effective solutions, develop and test them.
• Ability to analyze and deeply explore data to extract valuable insights; ability to visualize and communicate those insights.
• Proven experience in data science, with a strong understanding of optimization problems.
• Proficiency in Python and SQL, including data manipulation and feature engineering.
• Expertise in machine learning techniques and tools (e.g., CatBoost, XGBoost, TensorFlow, PyTorch, scikit-learn).
• English - Upper-Intermediate.

Will be a plus:

• The ideal candidate holds a MSc or PhD in Engineering, Statistics, Mathematics or related fields
• Familiarity with the AdTech domain.
• Experience with big data technologies (Spark, Hadoop) and processing large datasets.
• Hands-on experience with A/B testing and business metric optimization.
• Background in working with high-frequency or large-scale event data (e.g., 15B+ events daily).

Quantum is a global technology partner delivering high-end software products that address real-world problems. 

We advance emerging technologies for outside-the-box solutions; We focus on Machine Learning, Computer Vision, Deep Learning, GIS, MLOps, Blockchain, and more.

About the position

Quantum expands the team in Central Europe and has brilliant opportunities for Data Science Engineers. 

If you are interested in working on areas related to Data Analysis, fintech, image processing, and solving real-world challenges with innovative technologies, apply for the vacancy below. 

Must have skills:

• At least 1,5 years of commercial experience as a Data Science Engineer
• Strong knowledge of linear algebra, calculus, statistics, and probability theory
• Knowledge and experience with algorithms and data structures
• Strong experience with Machine Learning
• Expertise in areas of Computer Vision or Natural Language Processing
• Knowledge of modern Neural Networks architectures (DNN, CNN, LSTM, etc.)
• Experience with at least one of the Deep Learning frameworks (Tensorflow, PyTorch)
• Experience with SQL
• Strong knowledge of OOP
• At least an Upper-Intermediate level of English (spoken and written)

Nice to have skills:

• Experience with production ML/DL frameworks (OpenVino, TensorRT, etc.)
• Docker practical experience
• Experience with Cloud Computing Platforms (AWS, GCloud, Azure)
• Participation in Kaggle competitions

Your tasks will include:

• Full-cycle data science projects
• Data analysis and data preparation
• Development of Machine Learning / Computer Vision / Deep Learning / NLP solutions; Developing models and deploying them to production
• Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains

We offer:

• Delivering high-end software projects that address real-world problems
• Surrounding experts who are ready to move forward professionally
• Professional growth plan and team leader support
• Taking ownership of R&D and socially significant projects
• Participation in worldwide tech conferences and competitions
• Taking part in regular educational activities
• Being a part of a multicultural company with a fun and lighthearted atmosphere
• Working from anywhere with flexible working hours
• Paid vacation and sick leave days

Join Quantum and take a step toward your data-driven future.

Data Lab Scientist – Computer Vision

About Cyberette

Cyberette is an AI-native cybersecurity company developing forensic-grade technology to

detect digital manipulation in video, audio, and images. Our mission is to restore trust in

digital communication and protect organizations from deception in the AI era.

About the Role

We’re looking for a Data Lab Specialist with a solid background in data operations and

computer vision. You’ll be responsible for building and maintaining high-quality datasets that

fuel our detection models, ensuring accuracy, diversity, and consistency across all data

pipelines.

This role combines hands-on technical work with coordination — ideal for someone who

enjoys both creating structure and collaborating across teams.

Key Responsibilities

• Curate, collect, and annotate large-scale datasets for image and video analysis.

• Collaborate with the AI team to align data preparation with model goals.

• Ensure quality control and consistency across all dataset sources.

• Guide and coordinate junior team members or interns working on data tasks.

• Perform exploratory data analysis and identify dataset gaps or biases.

• Maintain clear documentation and versioning of data pipelines.

Requirements

• BSc/MSc in Computer Vision, Data Science, or related field.

• Proven experience with dataset preparation and management for machine learning.

• Strong understanding of computer vision principles and data labeling workflows.

• Proficiency in Python, Pandas and/or Polars, NumPy, and OpenCV.

• Experience working collaboratively with ML or research teams.

• Highly organized, detail-oriented, and dependable.

What We Value

Cyberette is built by a team of people who care deeply about purpose-driven innovation. We

believe in using AI to protect truth, identity, and digital integrity — and data is the foundation

of that mission.

Bonus Skills

• Familiarity with dataset tools (Label Studio, CVAT, Supervisely).

• Knowledge of multimodal or synthetic data generation.

• Understanding of ethical AI and dataset governance principles

Position Overview

As a Game Mathematician, you will own the mathematical design of our gaming systems — from core probability models to long-term behavioral dynamics of the game.

You will shape RTP, volatility curves, hit frequency, payout distributions, risk balance, and overall economic sustainability of each title.

This role requires deep theoretical knowledge, practical simulation skills, and the ability to collaborate closely with producers, designers, engineers, and compliance teams.

Responsibilities

• Develop and maintain detailed mathematical models for Slots, Crash Games, and Fast Games.

• Design and balance RTP, volatility, hit frequency, paytables, game curves.

• Model stochastic processes and RNG logic, ensuring correctness and predictability.

• Calculate probabilities and payout distributions across long-run simulations.

• Conduct large-scale simulations and statistical analysis of game behavior.

• Balance risk, retention, and economic KPIs of the product.

• Collaborate with producers to create optimal player experience.

• Work closely with engineers to validate correct technical implementation.

• Contribute to game logic design and innovative mechanics.

• Conduct competitive analysis of game mathematics and market trends.

• Participate in playtests and analyze real in-game behavior post-launch.

• Prepare complete mathematical documentation for certification and regulators.

Requirements

• Strong knowledge of probability theory, combinatorics, and mathematical statistics.

• Experience in slot or gambling game mathematics (3+ years).

• Practical experience designing and balancing RTP, volatility, and payout structures.

• Experience with stochastic modeling and simulations.

• Programming skills (Python, R, C++, MATLAB, or similar).

• Ability to clearly communicate mathematical decisions to cross-functional teams.

• English — Intermediate or higher.

Would Be a Plus

• Experience with crash or fast game mechanics.

• Experience with competitive math research.

• Understanding of player behavior and retention impact.

• Experience interacting with certification bodies and regulators.

What We Offer

• Direct influence on product economics and player experience.

• Real ownership of game mathematics and long-term performance.

• Competitive compensation.

• Professional growth inside a product-driven gambling studio.

• Flexible working format.

• Strong, collaborative team environment.

🚀AIMPROSOFT — Principal AI Platform Engineer Opportunity!

Aimprosoft is looking for a senior-level AI engineer who will design and lead the architecture of an enterprise-grade AI platform, evolving from an internal RAG-based assistant into a scalable, market-ready knowledge and automation product.

🎯About the role:

This is a principal-level role with high autonomy and architectural ownership. You will define the technical direction, key design principles, and long-term platform strategy for AI-powered knowledge discovery, semantic search, and business automation across multiple domains

🔑Core Responsibilities:

• Define the end-to-end architecture of an AI knowledge and automation platform
• Make independent decisions and lead the technical direction
• Design scalable retrieval systems beyond naive RAG implementations (semantic, document-level, process-level)
• Establish reasoning and orchestration patterns for multi-step business use cases
• Balance product vision, technical feasibility, and long-term maintainability
   

🔥What We Need From You:

• Proven experience designing production AI or search platforms from scratch
• Experience moving from single-use assistant to multi-domain, multi-use platforms
• API-first and platform-oriented system design
• Strong understanding of trade-offs in scale, latency, relevance, and cost
• Ability to design systems that remain explainable, debuggable, and governed
• Deep expertise in RAG, semantic search, and knowledge retrieval systems
• Vector databases, hybrid search, semantic indexing, and relevance ranking
• Architecture for document-, entity-, and process-level knowledge modeling
• Advanced LLM integration and reasoning design (structured, controlled, role-based)
• Proven experience with agent orchestration as a controlled architectural pattern including memory, tools, learning, task decomposition, etc
• Orchestration of AI workflows for automation use cases
• Experience with AI observability tools
   

📌 This Role Is Designed For Engineers Who:

• Enjoy thinking in platforms and long-term systems, not one-off features
• Are comfortable defining direction in ambiguous problem spaces where assumptions must be made explicit
• Care deeply about architectural clarity, system boundaries, and ownership
• Naturally reason about failure modes, trade-offs, and system limits
• Balance ambitious technical vision with practical constraints
• See governance, observability, and predictability as core parts of good engineering — not afterthoughts
   

💼What We Offer:

• A competitive salary that appreciates your skills and experience
• Cozy atmosphere and modern approaches. We have neither bureaucracy nor strict management nor “working under pressure” conditions
• Opportunity to implement your ideas, tools, and approaches. We are open to changes and suggestions aimed at improvement

Job Description

• 5-6 years of commercial experience, including at least 3 years in a related field;
• Strong knowledge and proven experience with Machine Learning, Computer Vision and Deep Learning;
• Technically strong with Python and/or other relevant programming experience;
• Ability to design and implement complex algorithms;
• Proficiency with numpy, scipy, opencv, tensorflow;
• Self manageable person, able to work without supervision;
• Experience in a field related to video analysis and/or processing;
• Bachelor's degree or equivalent in Computer Science, Engineering, Mathematics or a related field;
• Strong communication skills with Upper-Intermediate English level and ability to work under the pressure.

Job Responsibilities

We are seeking an experienced Senior Computer Vision Developer to join a collaborative initiative with our client's team, aimed at advancing and maintaining multiple real-time systems that leverage computer vision technologies. In this role, you will integrate seamlessly with both our internal team and the client's, contributing to a unified approach for enhancing system capabilities.

Your key responsibilities will involve developing and optimizing computer vision models, addressing existing bugs, and implementing new features that enhance system performance across various applications. You will be instrumental in supporting and evolving these systems to meet new challenges, working within a cross-functional team and contributing to a shared backlog.
 

Department/Project Description

Our client runs one of the most popular amusement parks in the world. The safety of their guests and cast members is the key to providing a seamless entertainment experience and our client was looking for ways to leverage the latest technology to take safety to the next level.

GlobalLogic helps the client create a flexible real-time AI-based attraction monitoring system to detect, alert, and record any discrepancy between the number of people detected by an overhead camera and the number of occupied seats from the seat sensor indicator lights.

About Cyberette
Cyberette is an AI-native cybersecurity company developing forensic-grade technology to detect digital manipulation across video, audio, and images. Our mission is to restore trust in digital communication and protect people, organizations, and institutions from deception in the AI era.

About the Role
We are looking for a Computer Vision Data Scientist with strong initiative and technical excellence to join our core development team. You’ll be responsible for designing, training, and optimizing computer vision models and architectures used in our deepfake detection and forensic analysis platform.

This role requires someone who thrives in fast-paced environments, loves solving complex problems, and brings both creativity and rigor to their work. You’ll collaborate closely with our founders and engineers to push the limits of multimodal AI for real-world impact.

Key Responsibilities

• Develop, train, and deploy computer vision models for image and video manipulation detection.
• Research and experiment with new architectures, model ensembles, and multimodal fusion techniques.
• Preprocess, clean, and manage large-scale datasets for training and evaluation.
• Optimize model accuracy, latency, and scalability for enterprise-grade performance.
• Contribute to the design of the model evaluation framework and internal benchmarking tools.
• Collaborate with other engineers and researchers to integrate models into production pipelines.
• Document methodologies, experiments, and findings clearly and systematically.

Requirements

• MSc/PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field.
• Strong experience in computer vision (CNNs, Transformers, multimodal models).
• Proficiency in Python and deep learning frameworks (PyTorch, TensorFlow).
• Solid understanding of ML ops, dataset curation, and model evaluation.
• Proven experience building and training models from scratch.
• Excellent analytical and problem-solving skills.
• Self-driven, disciplined, and collaborative mindset.

What We Value
At Cyberette, we believe technology should serve people. We are a team of builders united by a shared sense of purpose — creating tools that make the digital world safer and more truthful. If you care deeply about impactful innovation and want your work to matter, you’ll feel at home here.

Bonus Skills

• Experience with audio or multimodal analysis.
• Knowledge of adversarial attacks or deepfake generation methods.
• Experience in real-time inference or edge deployment.

Role Overview

Nucleus AI is seeking an AI / ML Data Scientist to help build and scale an AI-backed Learning Management System (LMS) that delivers personalized, adaptive learning experiences.

This is a hands-on, product-focused role at the intersection of machine learning, data science, and learning technology. You will design and deploy intelligent systems that directly impact learner engagement, personalization, assessment, and outcomes.

If you enjoy turning real-world data into models that are used by real users—and iterating on them in production—this role is for you.

Key Responsibilities

Machine Learning & Modeling

• Design, develop, and deploy machine learning models that power:
  • Personalized learning paths
  • Content and course recommendations
  • Learner analytics and insights
  • Adaptive assessments and feedback
     
• Build models for:
  • Learner skill inference and knowledge tracing
  • Engagement, completion, and drop-off prediction
  • Automated assessment scoring and feedback
     

Data & Analytics

• Analyze large-scale learner behavior data to extract actionable insights
• Develop and maintain data pipelines, feature engineering workflows, and model evaluation frameworks
• Apply statistical analysis and experimentation (including A/B testing) to validate model performance and impact
   

Collaboration & Product Integration

• Work closely with product managers, engineers, and instructional designers to translate learning objectives into AI-driven solutions
• Integrate models into production systems via APIs, batch pipelines, or real-time inference
   

LLMs & Advanced Techniques

• Experiment with and integrate LLMs and NLP techniques for:
  • Content generation
  • Learner feedback
  • Intelligent learner support
     
• Monitor models in production for performance, bias, and drift, and continuously improve them
   

Documentation & Governance

• Document models, assumptions, experiments, and results to ensure transparency, reproducibility, and maintainability
   

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, AI/ML, Statistics, or a related field
• Strong proficiency in Python and common ML libraries (e.g., scikit-learn, PyTorch)
• Solid understanding of:
  • Supervised and unsupervised learning
  • Feature engineering and model evaluation
  • Statistical analysis and experimentation
     
• Experience working with both structured and unstructured data
• Proficiency in SQL and working with large datasets
• Ability to clearly communicate complex technical concepts to non-technical stakeholders
   

Nice-to-Have Qualifications

• Experience building ML systems in ed-tech, LMS platforms, or learning analytics
• Familiarity with
  • Large Language Models (LLMs)
  • NLP
  • Recommendation systems
  • Knowledge graphs
• Experience deploying models to production environments
• Exposure to cloud platforms such as AWS, GCP, or Azure
• Understanding of learning science, instructional design, or assessment theory
• Experience with MLOps tools (model versioning, monitoring, CI/CD for ML)
   

What We Offer

• Opportunity to work on mission-driven AI that improves how people learn
• Ownership of ML systems used by real learners at scale
• A collaborative, cross-functional team culture
• Competitive compensation and benefits
• Flexible work location and schedule
• Continuous learning and professional growth opportunities

Junior Data Scientist/Quant Researcher Internship — 
Your Entry Point Into the World of High-Frequency Trading

Are you passionate about data analysis? Do you thrive on competitions, love solving unconventional problems, and want to test yourself in an industry where every nanosecond counts?

Join us for a paid internship at Atto Trading — an American HFT firm that builds high-frequency trading algorithms for U.S. financial markets.

💼 About Atto Trading — Where Engineering Meets Finance

Atto Trading is an American tech-driven trading company that builds and runs high-frequency, algorithmic strategies on financial markets.
 

We’re a small, focused team of engineers, traders, and researchers who:

• 💡 Turn ideas into profitable strategies
• 🇺🇸 Operate on U.S. financial markets
• 🧠 Constantly learn and tackle hard technical challenges together
• 🛠 Build ultra-fast, rock-solid software
   

As an intern, you won’t be stuck on side tasks — you’ll be a real part of the engineering team from day one.

🧠 During the internship, you will do:

• Analyze large datasets of market data using Polars, SQLAlchemy, scikit-learn, etc
• Build ipynb reports and interactive visualizations using Bokeh or Shiny-Plotly that provide real value
• Work with private analytical tools to create pipelines for subindicator generation
• Collaborate with engineers, traders, and analysts in a real-world business environment
   

📌 Program Details

• 🗓 Duration: 4 weeks, summer (August)
   
• 📍 Location: Ukraine in-office (Lviv) 
   
• 💼 Format: Paid internship
   
• 🏆 One top-performing intern will be offered a full-time or part-time role (depending on academic commitments)
   
• 🎁 The selected intern will receive an iPad as part of the welcome package from Atto Trading
  
   

This is a unique opportunity to gain real-world experience in high-frequency trading (HFT) — where analytics, precision, and speed determine success.

Please note: This internship is intended for candidates located in Ukraine. 

Please briefly describe your key achievements (academic, project-based, volunteer, or personal) in your CV.

Intro

ITSUA is a web development agency that builds a wide range of sites and web applications for clients worldwide. We are looking for a junior-level specialist to work directly with the manager on applied technical tasks within the company’s active projects.

Responsibilities

• Data collection, cleaning, normalization, and validation
• Writing SQL queries for data extraction and analysis
• Working with structured data (tables, CSV, JSON, APIs)
• Basic data analysis and report preparation
• Automation of data collection, cleaning, and analysis processes (scripts, pipelines, utilities)
• Research tasks: data discovery, source analysis, and exploration of tools
• Internal projects and processes automation

Recuirements

• Relational databases (solid SQL fundamentals; SELECT, JOIN, GROUP BY, filtering, etc.)
• Data workflows (ingestion, processing, output)
• Web technologies and APIs
• Python: basic/junior level (preferably pandas, working with data)
• Excel/GoogleSheets: formulas and careful data handling
• Attention to detail and accuracy, analytical and structured thinking
• General technical awareness and willingness to learn quickly
• English: B1 level or higher
• Active use of AI tools in daily work
• Interest in automation and process optimization
• Opportunity to grow towards data, automation, or engineering roles

Why ITSUA

• We work in small cross-functional squads without micromanagement
• Friendly environment with mentorship, professional growth, and English lessons
• Competitive salary

Automat-it is where high-growth startups turn when they need to move faster, scale smarter, and make the most of the cloud. As an AWS Premier Partner and Strategic Partner, we deliver hands-on DevOps, FinOps, and GenAI solutions that drive real results. We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for a hands-on Data Science Team Lead to build and scale production AI/ML solutions on AWS while leading a Data Scientist team. You’ll own the full lifecycle —from discovery and proof-of-concepts to training, optimization, deployment, and iteration in production — partnering closely with customers and cross-functional teams.

If you are interested in this opportunity, please submit your CV in English.

Responsibilities

• People leadership: Manage and coach a team of Data Scientists, set clear goals, run 1:1s, and support career growth and technical excellence.
• Delivery ownership: Drive project scoping, planning, and on-time, high-quality delivery from inception to production. Proactively remove blockers, manage risks, and communicate status to stakeholders.
• Customer engagement: Work directly with founders/technical leaders to understand goals, translate them into feasible AI roadmaps, and ensure measurable business outcomes.
• Model Development & Deployment: Deploy and train models on AWS SageMaker (using TensorFlow/PyTorch).
• Model Tuning & Optimization: Fine-tune and optimize models using techniques like quantization and distillation, and tools like Pruna.ai and Replicate.
• Generative AI Solutions: Design and implement advanced GenAI solutions, including prompt engineering and retrieval-augmented generation (RAG) strategies.
• LLM Workflows: Develop agentic LLM workflows that incorporate tool usage, memory, and reasoning for complex problem-solving.
• Scalability & Performance: Maximize model performance on AWS’s by leveraging techniques such as model compilation, distillation, and quantization and using AWS specific features.

• Collaboration: Work closely with other teams (Data Engineering, DevOps, MLOps, Solution Architects, Sales teams) to integrate models into production pipelines and workflows.

   

Requirements

• Team management experience: 2+ years leading engineers or scientists (people or tech lead).
• Technical experience: 5–6+ years in Data Science/ML (including deep learning/LLMs).
• Excellent customer-facing skills to understand and address client needs effectively.
• Expert in Python and deep learning frameworks (PyTorch/TensorFlow), and hands-on with AWS ML services (especially SageMaker and Bedrock).
• Proven experience with generative AI and fine-tuning large language models.
• Experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices.
• Fluent written and verbal communication skills in English.

• A master’s degree in a relevant field and AWS ML certifications are a plus.

   

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes

• Soft skills training

   

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognizing the value you bring to our team.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with the organization of the first Data Science UA conference, setting the foundation for our growth. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the role:
We are looking for a Computer Vision / Machine Learning Engineer to develop offline CV models for industrial visual inspection.

Your main task will be to design, train, and evaluate models on inspection data in order to:

• Improve discrimination between good vs. defect samples
• Provide insights into key defect categories (e.g., terminal electrode irregularities, surface chipping)
• Significantly reduce false-positive rates, optimizing for either precision, or recall
• Prepare the solution for future deployment, scaling, and maintenance
•  

Key Responsibilities:
Data Analysis & Preparation
- Conduct dataset audits, including class balance checks and sample quality reviews
- Identify low-frequency defect classes and outliers
- Design and implement augmentation strategies for rare defects and edge cases
Model Development & Evaluation
- Train deep-learning models on inspection images for defect detection
- Use modern computer vision / deep learning frameworks (e.g., PyTorch, TensorFlow)
- Evaluate models using confusion matrices, ROC curves, precision–recall curves, F1 scores and other relevant metrics
- Analyze false positives/false negatives and propose thresholds or model improvements
Reporting & Communication
- Prepare clear offline performance reports and model evaluation summaries
- Explain classifier decisions, limitations, and reliability in simple, non-technical language when needed
- Provide recommendations for scalable deployment in later phases (e.g., edge / on-prem inference, integration patterns)

Candidate Requirements:
Must-have:
- 1-2 years of hands-on experience with computer vision and deep learning (classification, detection, or segmentation)
- Strong proficiency in Python and at least one major DL framework (PyTorch or TensorFlow/Keras)
- Solid understanding of:

• Image preprocessing and augmentation techniques
• Classification metrics: accuracy, precision, recall, F1, confusion matrix, ROC, PR curves
• Handling imbalanced datasets and low-frequency classes

- Experience training and evaluating offline models on real production or near-production datasets
- Ability to structure and document experiments, compare baselines, and justify design decisions
- Strong analytical and problem-solving skills; attention to detail in data quality and labelling
- Good communication skills in English (written and spoken) to interact with internal and client stakeholders

Nice-to-have:
- Experience with industrial / manufacturing computer vision (AOI, quality inspection, defect detection, etc.)
- Familiarity with ML Ops/deployment concepts (ONNX, TensorRT, Docker, REST APIs, edge devices)
- Experience working with time-critical or high-throughput inspection systems
- Background in electronics, semiconductors, or similar domains is an advantage
- Experience preparing client-facing reports and presenting technical results to non-ML audiences

We offer:
- Free English classes with a native speaker and external courses compensation;
- PE support by professional accountants;
- 40 days of PTO;
- Medical insurance;
- Team-building events, conferences, meetups, and other activities;
- There are many other benefits you’ll find out at the interview.