20 beste vacatures voor de functie van machine learning engineer in 1315 almere (nieuwe medewerkers gezocht)

Senior Data Scientist - Commodity Trading and Risk Management
McKinsey & Company —Amsterdam
- Informatica
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- Master
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Effectory —Amsterdam Centrum
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- Flexibele werkuren
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eBay Inc. —Amsterdam
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- Doctor
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AI Engineer
MasORange —Amsterdam
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Tether Operations Limited —Amsterdam
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- Thuiswerk
- Bediening
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Senior Data Scientist (ML & Statistical Modelling)
Pacmed —Amsterdam Centrum
- Fulltime
- Hybride werken
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Senior Research Engineer (Based in Hong Kong)
Flow Traders —Amsterdam
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AI Research Engineer (Kernel & Inference Optimization) - 100% Remote Worldwide
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- Fulltime
- Thuiswerk
- Bediening
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AI- en Data Science Engineer
IntoData —Amsterdam
- Azure
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Accenture —Amsterdam
- Fulltime
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- Doctor
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5 dagen
Lead Data Scientist, Revenue - Ads, Revenue
Vinted —Amsterdam
- € 86.600 - € 127.400 per jaar
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- Engels
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- Mentale gezondheidszorgprogramma's
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Data Scientist
Xomnia —Amsterdam Centrum
- € 3.800 - € 6.200 per maand
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- Azure
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AI Research Engineer (Model Compression & Quantization)
Tether Operations Limited —Amsterdam
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Chapter Lead LLM / Agentic Expert
ARNVIND GROUP —Amsterdam
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Director Applied Science ADAS
TomTom —Amsterdam
- Fulltime
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Machine Learning Researcher – HFT
Durlston Partners —Amsterdam
- Tot € 750.000 per jaar
- Python

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Senior Data Scientist - Commodity Trading and Risk Management

McKinsey & Company -
Amsterdam

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Vacaturegegevens

Kwalificaties

CI/CD
Informatica
Supplychain
Logistiek
Onderzoek
Master
Pandas
Analytisch vermogen
Marktonderzoek
Bachelor
Continuous integration
Accountancy
Risicomanagement
APIs
Python

Volledige vacaturetekst

Job ID: 109606

Amsterdam

Brussels

Lisbon

Madrid

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You’ve come to the right place.

YOUR IMPACT

You will leverage your creativity and problem-solving skills to tackle clients’ most pressing issues using an analytical lens, meeting client needs and communicating your work to executive audiences.

Client counterparts span a wide range of audiences and functions from treasury and risk professionals, marketing & sales teams, procurement category managers, to high-level stakeholders (e.g., CFO). When working internally, you will build innovative algorithms and products (what we call “IP development”) to best meet our most common client needs, from building price forecasting models for commodities markets, to brainstorming and developing new offers and solutions to support future clients. You will also work with our engineers to design new interfaces to deliver faster, more impactful insights to our clients.

Your work on the team will primarily be in applying advanced analytics to enable better commodity risk management decisions. For example, you might work as the lead in maintaining and expanding existing hedging strategies by re-training existing models through process driven approaches. You might also modify and improve algorithm performance across market regimes, by introducing new features, data sources, and modelling approaches; rapidly identify opportunities for our clients to increase earnings potential and reduce downside risk by back testing various risk management strategies; co-build bespoke tools with client data science teams that tailor machine-learning algorithms to attain an optimal balance of earnings and volatility given clients’ risk appetite and capital constraints; and/or collaborate with and train cross-functional client teams to instill long-lasting capabilities and ensure new decision-making models are embraced by organizations.

You will receive best-in-class training in structuring business problems and serving as a client adviser and have opportunities to work closely with and learn from our senior commodity and risk practitioners, as well as industry players that are shaping the future of commodity markets and trading. You will get access to unparalleled career acceleration, with a huge amount of ownership and responsibility from the get-go in a collaborative, diverse, non-hierarchical environment. You will get the opportunity to travel to client sites, locally and around the world (once travel resumes). Lastly, you will be able to provide direct and measurable impact to some of the largest organizations in agribusiness, materials, energy, industrial, and consumer foods sectors around the globe.

As a member of the Commodity Analytics team, you will be based in one of the following offices: Brussels, Amsterdam, Madrid or Lisbon. You’ll work closely with McKinsey’s Commodity Trading Service Line to support clients across sectors and geographies.

Commodity Analytics helps commodity producers, processors, buyers, and traders across agriculture/softs, metals, energy, and consumer sectors improve commodity price risk capabilities with cutting-edge data science.

The Commodity Trading Service Line at McKinsey supports clients in commodity trading and risk strategy, trading operations transformation, and trading and risk digitization driven by deep trading experts with hands-on trading experience and advanced analytics assets.

Our Risk Practice supports clients in many different industries facing challenges of developing and implementing tailored concepts for risk.

YOUR GROWTH

Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.

In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues—at all levels—will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won’t find anywhere else.

When you join us, you will have:

Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
A voice that matters: From day one, we value your ideas and contributions. You’ll make a tangible impact by offering innovative ideas and practical solutions. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm’s diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you’ll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package, which includes medical, dental, mental health, and vision coverage for you, your spouse/partner, and children.

YOUR QUALIFICATIONS AND SKILLS

Required:

Undergraduate degree

Production-quality Python for model development, including optimization, time series forecasting, feature engineering, backtesting, and evaluation using standard DS toolkits (e.g., pandas, scikit-learn, statsmodels, gradient boosting, etc.)

Familiarity with pytest and reproducible research workflow; experience operationalizing models: versioned experiments, CI/CD, model monitoring and drift detection, and collaboration with engineering on APIs and model/solution design

Experience applying advanced analytical and statistical methods to solve business problems involving commodity markets

Ability to explain commodity market nuances and/or complex analytics approaches and results in layman’s terms to executive audiences across commodity trading, operations, supply chain / logistics, and finance / accounting functions

Preferred experience (all not expected):

Advanced degree in a quantitative discipline (computer science, applied mathematics, economics, quantitative finance, engineering) or equivalent practitioner experience

2+ years’ experience in commodity markets developing market research, trading, or hedging/risk management strategies such as netback/deal economics, signal backtesting, stress testing, and/or hedge effectivenes

2+ years’ experience in physical/cash markets of metals, power/electricity markets, natural gas, crude oil, refined products, and/or ocean freight

2+ years’ experience applying time series analysis of mean-reverting and cointegrated commodity prices/premiums (e.g., ARIMA, VECM, GARCH), supervised learning (e.g., SVM, LSTM, parallel or sequential tree-based models), unsupervised learning (e.g., PCA, K-means clustering), optimization (e.g., LP/MILP and stochastic models), and/or NLP sentiment analysis

6+ months’ experience with LLM-based analytics in enterprise settings (e.g., document/comms extraction, RAG, evaluation/guardrails)

Experience integrating data science and/or automation workflows with CTRM/ETRM systems via API

Experience automating middle/back-office processes with PRA and LLMs (e.g., pre-trade KYC/credit, trade execution, compliance, logistics, trade settlement)

Please review the additional requirements regarding essential job functions of McKinsey colleagues.

Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.

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Verfijn je zoekopdracht

machine learning engineer vacatures in 1315 almere

Senior Data Scientist - Commodity Trading and Risk Management

Mechanical Engineer

AI Inference Engineer QVAC (100% remote Worldwide)

Data Scientist (Clinical)

Senior AI/ML Engineer

Senior Data Scientist

Staff ML Engineer - Advertising

AI Engineer

AI Research Engineer (Model Compression & Quantization) - 100% Remote Worldwide

Senior Data Scientist (ML & Statistical Modelling)

Senior Research Engineer (Based in Hong Kong)

AI Research Engineer (Kernel & Inference Optimization) - 100% Remote Worldwide

AI- en Data Science Engineer

AI/ML Data Scientist

Lead Data Scientist, Revenue - Ads, Revenue

Data Scientist

AI Research Engineer (Model Compression & Quantization)

Chapter Lead LLM / Agentic Expert

Director Applied Science ADAS

Machine Learning Researcher – HFT

Ik wil de nieuwste vacature-alerts ontvangen voor de functie van machine learning engineer in 1315 almere

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