Задачи:
— Выявление производственных проблем и точек роста на основе данных;
— Участие в обследовании производственных участков, выезды в цеха, изучение технологических процессов на месте;
— Формализация производственных задач в цифровые кейсы: прогнозирование, классификация, детекция отклонений, контроль качества, оптимизация режимов;
— Сбор, выгрузка, очистка и консолидация данных из производственных и корпоративных информационных систем;
— Анализ данных технологических процессов, поиск закономерностей, факторов влияния и причин отклонений;
— Разработка, обучение и валидация ML-моделей для прогнозирования, оптимизации и поддержки принятия решений;
— Разработка и внедрение CV-решений;
— Подготовка датасетов, разметка данных, организация процессов сбора и актуализации обучающих выборок;
— Проверка гипотез, проведение пилотных проектов и оценка экономического эффекта;
— Визуализация результатов анализа, подготовка отчетов и рекомендаций для производственных подразделений;
— Взаимодействие с внутренними заказчиками, подрядчиками, интеграторами и смежными командами.
Требования:
— Практический опыт разработки и внедрения решений на базе ML;
— Практический опыт разработки и внедрения решений на базе Computer Vision;
— Опыт работы с производственными данными, временными рядами, журналами событий, технологическими параметрами;
— Опыт полного цикла работы с данными: сбор, выгрузка, очистка, анализ, построение признаков, обучение моделей, внедрение;
— Опыт проведения обследований производственных процессов и интервью с внутренними заказчиками;
— Понимание специфики промышленного предприятия и готовность работать “в поле”;
— Желателен опыт работы в металлургии, горнодобывающей промышленности, тяжелой промышленности, химическом производстве или энергетике;
— Понимание технологических процессов агломерационного, коксового или доменного производства будет преимуществом;
— Уверенное владение Python и библиотеками для ML/CV;
— Знание методов регрессии, классификации, кластеризации, поиска аномалий, анализа временных рядов, оптимизации, глубокого обучения;
— Опыт построения CV-моделей;
— Опыт работы с SQL и промышленными базами данных (MES, ERP, SCADA, historians, лабораторные системы, систем АСУ ТП);
— Понимание принципов интеграции моделей в промышленный ИТ-ландшафт;
— Опыт работы с Docker, Git, MLOps-инфраструктурой;
— Применение LLM в разработке решений;
— Понимание производственных показателей: качество сырья и продукции, производительность, простои, расход топлива и энергоресурсов, стабильность технологических режимов, надежность оборудования;
— Понимание причинно-следственных связей в производственном процессе и умение переводить экспертные знания технологов в аналитические модели;
— Навык оценки экономического эффекта от цифровых инициатив: снижение потерь, снижение брака, снижение простоев, рост производительности, снижение расхода ресурсов.
Условия:
— ДМС, включая стоматологию;
— Страхование жизни и страховка для путешественников;
— Корпоративная мобильная связь;
— Система скидок для сотрудников НЛМК ИТ;
— Частичная компенсация питания в корпоративных столовых;
— Возможность обучения за счет работодателя;
— Активная корпоративная жизнь;
— Поддержка от компании в жизненно важных событиях;
— Бесплатный доступ к электронной библиотеке.
- Придумывать новые подходы и алгоритмы, которые помогут растить долгосрочную выручку Авито; - Воплощать эти гипотезы в реальность, от проработки идеи до выкатки в production;
Location: Global
We are the creators of a new fintech era!
Our mission is to change this world by making blockchain accessible to everyone in everyday life. WhiteBIT is a global team of over 1,200 professionals united by one mission — to shape the new world order in the Web3 era. Each of our employees is fully engaged in this transformative journey.
We work on our blockchain platform, providing maximum transparency and security for more than 8 million users worldwide. Our breakthrough solutions, incredible speed of adaptation to market challenges, and technological superiority are the strengths that take us beyond ordinary companies. Our official partners include the National Football Team of Ukraine, FC Barcelona, Lifecell, FACEIT and VISA.
The future of Web3 starts with you: Join us as an Quantitative Researcher.
Requirements
Education & Experience:
— MSc or PhD in a quantitative field; a live trading track record outweighs credentials
— 5+ years in quantitative research or trading at a top-tier HFT firm, market maker, systematic fund, or crypto-native market maker; exchange-side market-structure experience is a plus
— Hands-on experience with at least one TradFi asset class (FX, futures, equities) and / or equivalent crypto asset classes; both maker and taker strategies
Core Technical Skills:
— Advanced probability, statistics, time-series analysis, optimization; strict validation discipline (multiple testing, out-of-sample hygiene, live–sim parity)
— Market microstructure: order-book dynamics, queue position, fill probability, adverse selection and markouts, market impact
— Expert Python (NumPy, pandas/Polars, PyTorch); working C++ or Rust for latency-critical components
— Tick-data engineering at scale: columnar stores, cross-venue normalization, data-quality control
Market Knowledge:
— Crypto microstructure: CEX matching engines and fee schedules, perpetuals (funding, mark price, liquidation/ADL), cross-venue arbitrage, DEX/AMM basics
— TradFi microstructure: FX ECN mechanics (firm vs last-look liquidity, prime brokerage), listed futures; low-latency architecture (tick-to-trade path, colocation, exchange protocols)
— Inventory and hedging: quoting models of the Avellaneda–Stoikov class and extensions, multi-asset inventory optimization, hedging, settlement workflows, real-time risk limits and kill switches
Exchange Microstructure & Mechanism Design:
— Maker-taker economics and market-quality measurement: fee-tier and rebate architecture, per-segment elasticity, spread/depth/slippage/markout metrics, defenses against rebate farming and wash trading
— Liquidity program design: obligation-based schemes (two-sided quoting, presence at touch, minimum depth, uptime) and incentive-based schemes (tiered rebates, credit lines, connectivity benefits)
— Maker protection and flow segmentation: markout-based counterparty scoring, retail price improvement (RPI) order types, asymmetric speed bumps and latency floors, minimum quote life, self-match prevention
— Exchange P&L modeling: net fee capture, subsidy budget and payback, LP unit economics from onboarding to self-sufficiency
Mindset & Soft Skills:
— Owner mentality with direct P&L accountability; ships to production and makes honest kill decisions
— Clear written communication with traders, engineers, exchange management, and external LPs
— Compliance discipline across crypto and TradFi market-abuse regimes.
Responsibilities
Responsibilities — Liquidity Program:
— Design the program end-to-end: MM tiers, admission criteria, obligations (max spread, min depth, uptime, presence at touch), incentives, and graduation to subsidy-free self-sufficiency
— Optimize the fee schedule for net capture: taker tiers priced to measured elasticity by segment; maker rebates funded from taker fees; safeguards against tier gaming
— Design order-book mechanics for comfortable quoting: tick and lot sizing, post-only / iceberg / RPI order types, self-match prevention, minimum quote life, passive-liquidity protection options
— Build the toxic-flow framework: markout-based flow classification, counterparty scoring, continuous monitoring, access rules or surcharges for consistently toxic takers
— Own the program financial model and roadmap: subsidy budget with payback targets; phases bootstrap → organic profitability → self-sufficiency; a market-quality dashboard as the single source of truth
Responsibilities — Trading Desc:
— Own the strategy roadmap — crypto first, then TradFi FX and futures; design pricing, quoting, hedging, and execution as one portfolio
— Run end-to-end alpha research on tick/order-book, cross-venue, funding/basis, and on-chain data
— Design the inventory-aware hedging framework, portfolio risk limits, and parameter governance
— Partner with engineering on low-latency implementation; validate in high-fidelity simulation and canary deployments
— Own P&L attribution, TCA/markout analysis, and research standards
— Lead the TradFi FX entry research workstream (LSEG FX Spot Matching, Euronext FX).
Working terms
Immerse yourself in Crypto & Web3:Master cutting-edge technologies and become an expert in the most innovative industry.
Master cutting-edge technologies and become an expert in the most innovative industry.
Work with the Fintech of the Future:
Develop your skills in digital finance and shape the global market.
Take Your Professionalism to the Next Level:
Gain unique experience and be part of global transformations.
Drive Innovations:
Influence the industry and contribute to groundbreaking solutions.
Join a Strong Team:
Collaborate with top experts worldwide and grow alongside the best.
Work-Life Balance & Well-being:
Modern equipment.
Comfortable working conditions, and an inspiring environment to help you thrive.
24 calendar days of paid leave.
Additional days off for national holidays.
With us, you’ll dive into the world of unique blockchain technologies, reshape the crypto landscape, and become an innovator in your field. If you’re ready to take on challenges and join our dynamic team, apply now and start a new chapter in your career!
Let’s Build the Future Together!
WhiteBIT offers all candidates an equal opportunity to join the team. All hiring decisions are made without regard to race, national origin, gender identity or sexual orientation, age, religion, disability, medical condition, marital status, familial status, veteran status, or any other legally protected characteristic of an individual.
— Разработка поведенческих моделей для сегментов ФЛ по основным продуктам банка. — Знание основных алгоритмов и методов ML и анализа данных: линейные модели, ансамбли, временные ряды, классификация и кластеризация.
TBC Uzbekistan is a digital financial services ecosystem powering some of Uzbekistan's most innovative financial experiences.
Languages required: English (C1), Russian (B2).
Work format: On-site in Tashkent, Uzbekistan.
Location: Remote
About the Team:
Netlify’s Data team helps the company understand and improve the full product-led growth journey, from activation and engagement through conversion, retention, and monetization. We partner closely with Product, Engineering, and Growth to uncover opportunities, evaluate investments, and understand what drives customer and business outcomes.
We’re hiring a Senior Staff Data Scientist to deepen how data shapes our product and growth strategy. You’ll develop an end-to-end understanding of the PLG journey, proactively identify opportunities, and turn complex data into hypotheses, experiments, and recommendations that influence where we invest and what we build. This is a highly autonomous role for someone who can move from identifying an important question to shaping the approach, defining success, and driving toward an answer.
What You'll Do:
Own the analytical understanding of Netlify’s PLG performance across activation, engagement, conversion, monetization, and retention, identifying opportunities before they become requests
Partner with Product and Engineering leadership to turn behavioral insights into product bets, defining what to test, how to measure it, and what the results mean
Lead experimentation from hypothesis through decision, including study design, methodology, success metrics, guardrails, analysis, and recommendations
Apply statistical rigor where it matters while recognizing when there is enough signal to make a decision and move forward, and help teams develop that same judgment
Build scalable analytical systems like semantic models, trusted metrics, proactive monitoring, and AI-powered agents that surface opportunities without waiting to be asked
Use AI to investigate faster, automate recurring analytical work, and test more hypotheses without sacrificing the judgment that makes the output useful
Identify gaps in measurement, event instrumentation, and metric definitions, and partner with Data and Product Engineering to close them
Serve as a trusted analytical partner to PLG leadership, using evidence and product judgment to influence investment decisions and roadmap priorities
Influence product strategy through evidence, product instincts, and a clear point of view, without relying on formal authority to do it
What You'll Bring:
8+ years of experience in product analytics, growth analytics, or data science, with a track record of high ownership and measurable impact on PLG or consumer product outcomes
Deep understanding of product and growth dynamics across activation, engagement, conversion, monetization, and retention
Demonstrated ability to turn behavioral data into product hypotheses and carry them from insight through experimentation and measured outcomes
Deep experimentation expertise: study design, statistical reasoning, causal inference, and the judgment to know when an experiment has told you what you need to know
Experience building analytical systems such as metrics layers, monitoring frameworks, or semantic models that teams can rely on over time
An AI-native approach to analysis: you use AI tools actively to accelerate investigation, automate repetitive work, and surface patterns faster
A track record of influencing senior stakeholders and product direction through analytical reasoning, clear recommendations, and sound judgment
Comfort operating with significant autonomy in ambiguous problem spaces, including determining which questions are most important to answer
Strong written and verbal communication skills in distributed environments, with the ability to make complex findings clear and recommendations actionable
This Role is a Great Fit If:
You're energized by finding the opportunity before anyone thought to ask - proactive discovery is how you naturally work, not a mode you shift into
You think like a product person who happens to be exceptionally rigorous with data, not a data person who occasionally weighs in on product
You thrive when the problem isn't handed to you - you'd rather define the question worth asking than answer the one that landed in your queue
You get excited about building systems that keep working after you've moved on to the next problem
You're comfortable making a call with imperfect information and can articulate clearly why you made it
You enjoy being a thought partner to senior leaders - shaping how they think about investment and opportunity, not just supporting decisions already made
You work well in a remote-first, async environment where written clarity and self-direction matter more than proximity
You're drawn to roles where the measure of success is outcomes, decisions made, bets tested, metrics moved, not volume of output produced
Applying
Not sure you meet 100% of our qualifications?
Please apply anyway!
When applying please include:
A resume or short listing of your job history & skills (link to a LinkedIn profile would be fine). We appreciate a cover letter explaining why you would enjoy working in this role at Netlify to get to know you a bit better, though this is not required and will not impact your application. Our mission is to “build a better web” and that cannot be done without a diversity of skill sets, backgrounds and thoughts.
Of everything we've ever built at Netlify, we are most proud of our team. Netlify is an Equal Opportunity Employer. We are devoted to building a team of people with diverse backgrounds and lifestyles. Driving equality empowers our team, enables us to innovate, and helps us maintain a more inclusive environment. We don’t discriminate against employees or applicants based on gender identity or expression, sexual orientation, religion, age, race, military/veteran status, citizenship, pregnancy status, or any other differences. If we can do anything to provide a better interview, i.e. accommodate a disability, then please let us know by emailing
accommodations@netlify.com
.
About Netlify
Netlify is the most popular way to build, deploy, and scale modern web applications, empowering everyone from fast moving solo developers to enterprise teams. Millions of developers and organizations rely on Netlify as their platform of choice for composing web applications that are production ready, performant, and flexible. Now, as we embrace the next era of software development, we are embedding the same fluid, intuitive experience into the Agent Experience (AX), making it just as simple for intelligent agents to understand, interact with, and act on our platform as it is for developers. Whether your user is human or machine, Netlify ensures the path from idea to URL is seamless, fast, and deeply reliable.
We are a Series D company that has raised over $200M from investors such as Andreessen Horowitz, Kleiner Perkins, EQT, Bessemer, BOND, and Menlo Ventures. As a fully distributed company, we aim to create a company culture where the best idea can come from anywhere and strive to be thoughtful, compassionate, and collaborative in our work. If this sounds like something you’d like to be part of, we’re excited to connect with you!
At Netlify, we are committed to a compensation philosophy that prioritizes fairness and equity, positions our employee compensation competitively in the market, recognizes and rewards performance, and takes a comprehensive approach to our rewards package. We anchor our compensation philosophy on a market-based approach, therefore salary ranges may differ depending on the labor cost in a particular location. The salary provided is in addition to robust benefits and participation in Netlify’s equity plan. Our hiring range for this role is targeted at $204,000 - $275,000 for most US-based locations. Candidates outside the US or in premium markets should consult with their Talent Acquisition partner regarding location-based ranges, as they may be higher or lower than the average US range listed. The starting pay will be determined based on multiple factors, including expertise and skills, market demands, experience, internal equity, and applicable geographic location. These compensation packages and ranges are subject to change and may be modified in the future.
— кандидатов с опытом работы от 3,5 лет в крупных российских и международных IT-, BigTech- и FinTech-компаниях. — с опытом полного цикла разработки моделей: от ресёрча до выкатки в продакшен.
анализ данных и проверка гипотез для решения бизнес-задач; разработка и валидация ML-моделей (регрессия, классификация, кластеризация, ансамбли) feature engineering: подготовка и проектирование признаков;
Разрабатывать и улучшать модели рекомендаций и ранжирования для разных пользовательских сценариев: рекомендации заведений на карте, поиск по категориям, персональные подборки. Формулировать и проверять продуктовые и ML-гипотезы: проводить офлайн-оценку моделей и участвовать в A/B-тестах.
Тебе предстоит решать исследовательские и прикладные задачи: от анализа данных и разработки метрик до создания, внедрения и сопровождения алгоритмов. Чем предстоит заниматься Анализировать и обрабатывать данные различного объёма и структуры.
