Jobs Data Science

We’re looking for a Senior Data Scientist to join a fast-growing R&D team working with large-scale, real-time data in the AdTech domain.

This is not a pure research role — we need someone who can take ownership end-to-end: from idea → modeling → production.

About the Role

You’ll work on high-load systems processing billions of requests, building data-driven solutions that directly impact large-scale digital products and decision-making.

Responsibilities

• Analyze large-scale, complex datasets to uncover insights and opportunities
• Design and build scalable data pipelines
• Develop and deploy ML models (classification, regression, recommendation systems)
• Work with real-time (online) data processing systems
• Improve existing data products and create new ones
• Collaborate with Product, BI, Engineering, DevOps, and Marketing teams
• Own the full lifecycle: research → implementation → production → monitoring

Requirements (Must-have)

• 4+ years of experience as a Data Scientist (6+ preferred)
• Proven experience in AdTech / programmatic advertising
• Hands-on experience with high-load systems (billions of requests)
• Experience working in real-time environments
• Strong background in Machine Learning (tree-based models, recommendation systems)
• Solid Python skills with ML libraries (e.g., XGBoost, LightGBM)
• Strong SQL and data querying skills
• Experience with monitoring tools (e.g., Grafana, Kibana)
• Ability to work end-to-end (research → production)
• English level: C1 (Advanced) with strong communication skills

Nice to Have

• Deep understanding of AdTech ecosystem (DSPs, SSPs, Ad Exchanges)
• Experience with databases like Vertica, VoltDB, MongoDB

• Familiarity with PMML

   

  Hiring Process

• Technical interview
• Home assignment
• HR interview

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

Project

The project focuses on a deep refactoring and optimization of the reporting ecosystem combining Salesforce CRM and Tableau. The main goal is to redesign current data flows, replacing the bulky and slow architecture with a modular system of reusable components. You will work on a process redesign to ensure speed, data accuracy, and ease of future system maintenance.

Responsibilities

• Development and Redesign: designing and supporting complex interactive visualizations in Tableau Desktop with a focus on modularity.
• Architecture Optimization: transforming bulky data flows into a fast and stable reporting system.
• Integration and Setup: working with data streams from Salesforce CRM and ERP systems (SAP, Odoo, MS Business Central).
• Technical Optimization: performance tuning (Data Extracts, calculated fields, SQL query optimization).
• Business Collaboration: gathering requirements from stakeholders and translating them into clear technical specifications for visualization.
• Data Governance: ensuring data accuracy, integrity, and security (including Row-Level Security).

Requirements

• Must-have:
  • 1.5-2+ years of commercial experience with Tableau (Desktop, Server/Cloud) or other BI tools.
  • Strong SQL skills (writing complex queries, joins, CTEs).
  • Understanding of CRM and ERP system architecture (how data is stored and interconnected).
  • Intermediate+ English level (for technical communication and documentation).
• Nice-to-have:
  • Experience with Tableau and Salesforce integration (a significant plus).
  • Experience with Tableau Prep or other ETL tools (Alteryx, KNIME).
  • Tableau Desktop Specialist or Certified Data Analyst certification.
  • Experience with cloud data warehouses (Snowflake, BigQuery, AWS Redshift).

Conditions

• Collaboration Type: Part-time (Freelancer / Contract).
• Location: Remote.
• Schedule: Flexible (details to be discussed based on your availability).

Selection Process

1. Recruiter screening.
2. Technical interview with the Tech Lead.
3. Offer.

Evowill is looking for a Data Science Mentor to join our team. If you’re excited to share your knowledge with beginners in data science and machine learning, and enjoy teaching or want to try yourself in this role, we would be happy to collaborate!

You are:

• A Data Scientist/Data Analyst with 3–5+ years of experience in Data Science, Machine Learning, or Data Analytics;
• Patient, responsible, and well-organized;
• Interested in teaching and knowledge sharing;
• Curious and eager to learn, just as much as to teach;
• Proficient in writing clean, readable, and reproducible code;
• Passionate about helping others grow technically and intellectually;

• Comfortable working remotely with a flexible schedule (Ukrainian timezone).

   

We are:

• A Ukrainian-Colombian team;
• Working with Python, Data Science, and AI-related projects;
• Supported by experienced mentors who will help you onboard;

• Focused on growth, learning, and continuous improvement.

   

Technical skills:

• Strong proficiency in Python for data analysis;
• Hands-on experience with NumPy, Pandas, and Scikit-learn;
• Experience with both structured and unstructured data
• Solid understanding of machine learning concepts (classification, regression, clustering);
• Knowledge of statistics, basic and modern modeling techniques;
• Experience with Jupyter Notebooks or similar tools;
• Data handling skills: cleaning, preprocessing, and visualization (Matplotlib, Seaborn, or similar);
• Experience working with databases (SQL/NoSQL);
• Experience with XGBoost and Deep Learning models
• Experience with deep learning frameworks (TensorFlow, PyTorch, Keras);
• Familiarity with big data tools (e.g., Spark, BigQuery).
• Experience in NLP tasks such as topic modeling
• Understanding of embeddings, vector databases, and language models

• English — Upper-Intermediate or higher.

   

Nice to have:

• Experience with Git;
• Basic understanding of MLOps is a plus;
• Experience with cloud platforms (AWS, GCP, Azure);
• Experience deploying ML models;

We offer:

• Remote and flexible work;
• An international team (Ukraine + Colombia);
• Part-time opportunity;
• Professional growth;
• A supportive and collaborative environment.

Role overview

Partner with sales and delivery to win new data engagements. You'll translate vague client problems into credible, costed solution architectures, lead technical discovery, and present to stakeholders ranging from CTOs to procurement.

Responsibilities

• Lead technical discovery calls; turn business needs into reference architectures and high-level designs
• Build proposals, SoWs, and effort estimates jointly with delivery leads
• Run solution demos, POCs, and architecture walkthroughs for prospects
• Respond to RFPs/RFIs with clear technical narratives
• Stay current on the modern data stack and competitor offerings; advise sales on positioning and trade-offs

Required experience

• 5+ years in data engineering / data architecture, with at least 2 years in a client-facing or presale capacity
• Strong command of cloud data platforms across AWS, Azure, and GCP (at least two hands-on)
• Working knowledge of the major data warehouses and lakehouses: Snowflake, Databricks, BigQuery, Redshift
• Solid grasp of streaming (Kafka, Kinesis), orchestration (Airflow, dbt, Dagster, Prefect), and table formats (Delta, Iceberg)
• Comfortable estimating cost, effort, and risk across architectures you haven't personally built
• Excellent written and spoken English; able to lead a room of senior stakeholders

Nice to have

• Background in BI tooling (Power BI, Tableau, Superset)
• Experience with regulated industries (banking, insurance, healthcare)
• Certifications across two or more cloud/data vendors

We are looking for a Computer Vision Engineer with solid ML/DL experience to join our team on challenging projects.
We consider engineers at Middle and Senior levels - tasks and responsibilities will be adjusted accordingly. 

Required Qualifications:

• 3+ years of experience in computer vision
• High proficiency in Python
• Strong experience with deep learning and the PyTorch framework for computer vision tasks
• Research experience in computer vision with a focus on delivering results
• Ability to work independently or within a small team, with a strong sense of ownership over results

Nice to Have:

• Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
• Understanding of geometric computer vision principles
• Model optimization: quantization, pruning, neural network compilers
• Hands-on experience implementing low-level CV algorithms
• Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
• Knowledge of C++

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.

Join PwC's Data & AI team and help design and deliver the AI and machine learning solutions that drive real business impact. We're growing quickly due to a strong pipeline of client work, and we're hiring across multiple seniority levels — from junior to senior Data Scientists.

Python is the core skill we expect. Depending on your strengths, you may focus on machine learning, statistical modelling, NLP, computer vision, or GenAI. Many roles also include "full-solver" flexibility — contributing where needed, including experimentation, prototyping, deploying models, or working end-to-end on AI use cases using modern platforms (including Microsoft technologies where relevant).

What You'll Do:

• Build AI That Solves Real Problems: Design, develop, train, and evaluate machine learning and statistical models across a wide range of business challenges.
• Turn Messy Data Into Insights: Explore, analyse, and visualize complex datasets to uncover patterns that matter. Perform feature engineering, data preprocessing, and selection to maximize model performance.
• Push the Boundaries With GenAI & NLP: Design and implement solutions leveraging Large Language Models, Retrieval-Augmented Generation (RAG), and NLP techniques.
• Experiment Rigorously, Deploy Confidently: Collaborate with data engineers and platform teams to move models from notebook to production, monitor performance over time, and support continuous retraining and improvement.
• Work Directly With Clients: Collaborate with clients across Western Europe and the USA to understand their business challenges, frame problems as data science opportunities, and communicate findings clearly. 
• Stay Ahead of the Curve: Keep up with the latest in AI/ML research, emerging techniques, and new tools. 

Who We're Looking For:

• Programming Skills (Key Requirement): Strong programming skills in Python (e.g. scikit-learn, TensorFlow, PyTorch, pandas, NumPy, Hugging Face, LangChain). The ability to write clean, maintainable, and reproducible code is essential.
• Machine Learning: Demonstrated hands-on experience building, training, and evaluating ML models. Strong understanding of supervised and unsupervised learning techniques, model selection, hyperparameter tuning, and cross-validation.
• Statistics & Mathematics: Understanding of core statistical concepts, probability, and linear algebra.
• NLP & GenAI (Highly Valued): Experience with natural language processing, text analytics, large language models, prompt engineering, RAG architectures, or other GenAI techniques.
• Computer Vision (Nice to Have): Experience with image processing, object detection, visual reasoning, or satellite imagery analysis is an advantage.
• Data Handling: Proficiency in SQL and experience with data wrangling, cleaning, and transformation.
• Cloud & MLOps (Nice to Have): Experience with cloud platforms (preferably Azure: Databricks, Azure ML, Synapse) or similar services on AWS/GCP is an advantage.
• Professional Background: At least 2–3 years of professional experience in data science, machine learning, applied research, or similar analytical roles.
• Language Skills: English at B2 level or higher.

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

About the role

We are looking for a Senior Data Scientist to lead the evolution of machine learning systems within a high-scale AdTech ecosystem.

This is not a “campaign optimization” role. You will work on the core decision-making systems (DSP level) — where pricing, bidding, pacing, and experimentation interact in real time across billions of events per day.

You will be shaping the “brain” of the platform: a set of interconnected systems where small improvements can have a large business impact.

What you’ll work on

• Pricing & Budget Scalability
  Scale budgets while maintaining performance and controlling overspend
• User Selection Optimization
  Improve CVR through smarter targeting and traffic selection
• Exploration Efficiency
  Reduce wasted spend while preserving learning
• Incrementality Measurement
  Measure true lift vs attributed performance
• Fraud Detection & Filtering
  Improve traffic quality and filtering strategies

What we expect from you

System-level thinking

• Ability to reason about interacting systems, not isolated models
• Understanding of:
  • auction dynamics
  • bidding vs pacing trade-offs
  • feedback loops between models
• Seeing problems beyond segmentation or heuristics

Strong experimentation mindset

• Designing experiments, not just running A/B tests
• Experience with:
  • metric design (proxy vs north star)
  • online vs offline evaluation gaps
  • interference and auction effects
• Ability to translate system changes into measurable impact

Ownership & impact

• Proven track record of driving business impact, not only building models
• Ability to explain:
  • expected vs actual impact
  • why results differ
• Performance accountability mindset

AdTech domain understanding

• Solid understanding of:
  • targeting vs bidding vs supply dynamics
• Experience working close to DSP / auctions/pricing systems

Collaboration maturity

• Ability to work across DS, MLE, and Product
• Understanding trade-offs and constraints
• Experience making decisions in ambiguous environments

Core responsibilities

• Turn ambiguous problems into testable hypotheses
• Design and run offline analysis + online experiments
• Use intermediate metrics to understand system behavior
• Build prototypes and iterate quickly
• Identify where system-level improvements are required
• Collaborate across teams to drive end-to-end impact

Requirements

• 5+ years in Data Science / Machine Learning
• Strong experience in high-frequency systems (AdTech / FinTech / similar)
• Python & SQL proficiency
• Experience with big data tools (Spark, Snowflake, etc.)
• Strong ML background (TensorFlow, PyTorch, or similar)
• Solid foundation in:
  • probability
  • statistics (frequentist / Bayesian)
  • causal inference
• Master’s or PhD in a quantitative field

Nice to have

• Experience with DSP / auctions / pricing systems
• Experience with large-scale experimentation

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.

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

Шукаємо Mid / Senior Graph Analytics Engineer для виконання завдань з аналізу графів, виявлення спільнот, аналізу мереж шахрайства, реалізації системи розслідувань, візуалізації графів та підтримки аудиторського сліду.
 

Стек: 
Louvain community detection, NetworkX, BigQuery Graph Analytics, AppSheet або еквівалентні інструменти / підходи для візуалізації графів, робота з дводольним графом provider–member–pharmacy
 

Обов'язки:
• Виконувати graph analytics для fraud network analysis
• Реалізовувати Louvain community detection
• Працювати з дводольним графом provider–member–pharmacy
• Використовувати D4 cross-provider graph з R5, без перебудови
• Будувати Investigation System за R2 BRD на AppSheet або еквіваленті
• Підтримувати схему справи: ідентифікатор кластера, постачальники, члени, SAR, що підлягають ризику, пакет доказів
• Створювати візуалізацію графів для слідчих
• Забезпечувати регуляторний аудиторський слід
• Реалізовувати позначення аптек поза мережею
 

Ключові результати:
C1–C3: виявлення спільнот, аналіз графів, побудова системи розслідування, візуалізація, аудиторський слід та позначення аптек.

Шукаємо ML-спеціаліста для розробки предиктивних моделей на основі великих табличних датасетів. Задачі пов’язані з прогнозуванням користувацької поведінки та метрик на ранніх етапах життєвого циклу.

Вимоги:

• 3+ роки досвіду в ML / Data Science
• Сильний досвід роботи з табличними даними (обов’язково)
• Впевнений рівень SQL (бажано BigQuery) та досвід роботи з великими датасетами
• Практичний досвід побудови моделей прогнозування (regression / prediction / ranking)
• Досвід роботи з моделями: CatBoost, LightGBM, XGBoost
• Сильні навички feature engineering (категоріальні, часові, поведінкові ознаки)
• Розуміння часової природи даних (train/validation split, data drift)
• Розуміння проблем data leakage та методів його уникнення
• Досвід роботи з незбалансованими розподілами та складними таргетами (long-tail, zero-inflated)
• Розуміння когортного аналізу та часових залежностей у даних
• Досвід побудови reproducible ML pipeline (навчання, інференс, версіонування)
• Відмінні комунікативні навички та ділове володіння англійською мовою

Буде плюсом:

• Досвід роботи з Google Cloud (BigQuery, GCS тощо)
• Досвід роботи з mobile або subscription продуктами
• Досвід прогнозування користувацької поведінки, retention або revenue
• Досвід роботи з маркетинговими або атрибуційними даними
• Досвід розробки та деплою ML-моделей у production
• Розуміння batch inference та підходів до масштабування моделей

Обов’язки:

• Розробка та навчання ML-моделей на табличних даних (user-level та агреговані дані)
• Побудова складного feature engineering
• Робота з часовими даними (коректні split, врахування drift)
• Контроль і запобігання data leakage
• Робота зі складними таргетами та нерівномірними розподілами
• Оцінка якості моделей на різних рівнях (окремі спостереження та агрегати)
• Побудова та підтримка reproducible ML pipeline (навчання, інференс, версіонування)
• Оптимізація моделей та підбір підходящих алгоритмів
• Аналіз та структурування великих обсягів даних
• Безперервне вдосконалення підходів до моделювання та роботи з даними

Ми пропонуємо:

• ЗП $2500 - 4000;
• Своєчасна заробітна плата;
• Можливість кар'єрного росту;
• Оплачувана відпустка;
• Молодий дружній колектив;
• Круті корпоративні заходи;
• Затишний офіс;
• Ігрова приставка та настільний теніс в офісі;
• Стандартні плюшки — чай, кава, смаколики;
• Зручний графік з 10:00 до 19:00.

Ми — компанія з 9-річним досвідом розробки Custom Software Solutions, що спеціалізується на Data Engineering та AI-інтеграціях.

Requirements:

• Previous experience technicaly leadings teams.

• 5+ years of experience in Data Science;
• 4+ years of commercial experience with Python;
• People management skills;
• Deep understanding of algorithms and data structures;
• Solid knowledge of Machine Learning and Data Science methodologies;
• Hands-on experience with LLMs, RAG pipelines, and LangChain;
• Experience with Docker, Kubernetes, and CI/CD workflows;
• Understanding of multithreading and multiprocessing approaches;
 

Nice to have:

• Experience with Databricks and Snowflake;

Responsibilities:
• Design and develop scalable DS architectures;
• Lead AI and Data Science projects end-to-end;
• Develop maintainable, production-ready solutions;
• Contribute to architectural decisions and technical strategy;
• Drive R&D initiatives and evaluate emerging AI technologies;
• Maintain high engineering and coding standards.

What we offer:

• Opportunity to work on cutting-edge AI projects;
• International clients and technically challenging tasks;
• Professional growth and leadership opportunities;
• Competitive compensation in USD;
• Flexible work schedule and remote-friendly environment;
• Paid vacation, sick leave, and medical insurance;
• Supportive team culture with minimal hierarchy.