machine learning scientist

Latent Labs

<div>
 The Opportunity
 <br/>
 <br/>
 We are looking for a highly skilled machine learning researcher with significant experience in generative modeling. You will join an interdisciplinary team of machine learners, protein engineers and biologists, jointly working to change the way that we control biology and cure diseases. In your role you will architect novel generative models with the goal of designing new proteins that are functional in wet lab assays.
 <br/>
 <br/>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You are a strong ML researcher with experience in generative modeling. You have led or worked on notable machine learning projects, as documented by your contributions to widely used open source libraries, significant product launches or high impact publications, e.g. at NeurIPS, ICML, ICLR or Nature venues. You have a proven track record of deep expertise in generative modeling.
  </li>
  <li>
   You are a skillful ML developer. You write ML code that is robust, tested and easy to maintain. You have experience using version control and code review systems. You are a fast prototyper and hacker who can also write beautiful production code. You have experience running training and inference on cloud hardware, parallelizing data and models across accelerators.
  </li>
  <li>
   You are a data engineer. You have experience building ML data pipelines for the training and evaluation of deep learning models. You are able to analyze the raw data, construct appropriate dataset splits and build pipelines that perform and scale.
  </li>
  <li>
   You are passionate about model performance. You have an intricate understanding of how ML libraries interplay with hardware and data and love to optimize deep learning models for training / inference speed. You have a deep knowledge of best principles and tricks in architecting deep learning models and use it to optimize how they perform on validation metrics.
  </li>
  <li>
   You are mission driven and curious. You are passionate about making a positive impact on the world, whether it's for patients, customers or beyond. You are motivated by the end goal and are flexible in adapting to different approaches and methodologies. You are curious about problems, however small or big they appear. You thrive in a dynamic environment. You work well in a fast-paced setting where goals must be achieved efficiently and urgently.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What Sets You Apart
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   You have experience in computational biology or protein design. You have worked on ML-driven projects in biology.
  </li>
  <li>
   You have a natural science background. You are academically trained in physics, biology, chemistry or other related fields.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Your Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Build machine learning models that work in the physical world [~90% of your time]:
  </li>
  <ul>
   <li>
    Contribute to a careful curation of our training and evaluation data.
   </li>
   <li>
    Propose and build ML evaluation metrics that align with real world success and company goals.
   </li>
   <li>
    Quickly prototype generative models against our lead metrics and perform deep analyses of improvements.
   </li>
   <li>
    Collaborate in a joint codebase with other research scientists, engineers and protein designers, maintaining highest code standards.
   </li>
   <li>
    Contribute to the maintenance of our compute and ML development infrastructure.
   </li>
   <li>
    In collaboration with the bio team, plan wet lab testing campaigns and carry out model inference against biological targets to enable their testing in the wet lab.
   </li>
   <li>
    Quickly learn from wet lab results and feedback data to our models.
   </li>
  </ul>
  <li>
   Self development [~10% of your time]:
  </li>
  <ul>
   <li>
    Stay on top of the latest developments in ML.
   </li>
   <li>
    Gain a strong working understanding of protein and cell biology.
   </li>
   <li>
    Participate in knowledge sharing, e.g. organize and present at our internal reading group.
   </li>
   <li>
    Attend and present at conferences.
    <br/>
   </li>
  </ul>
 </ul>
 <strong>
  Apply
  <br/>
  <br/>
 </strong>
 We offer strongly competitive compensation and benefits packages, including:
 <br/>
 <br/>
 <ul>
  <li>
   Private health insurance
  </li>
  <li>
   Pension/401(K) contributions
  </li>
  <li>
   Generous leave policies (including gender neutral parental leave)
  </li>
  <li>
   Hybrid working
  </li>
  <li>
   Travel opportunities and more
   <br/>
   <br/>
  </li>
 </ul>
 We also offer a stimulating work environment, and the opportunity to shape the future of synthetic biology through the application of breakthrough generative models.
 <br/>
 <br/>
 We welcome applicants from all backgrounds and we are committed to building a team that represents a variety of backgrounds, perspectives, and skills.
 <br/>
 <br/>
</div>


Machine Learning Scientist

Accenture

<div><p><b>YOU ARE</b></p><p>
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree or equivalent</li></ul><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul><p><b>
PREFERRED QUALIFICATION</b></p><ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div>

AI/ML Computational Science Manager

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Amazon Strategic Account Services (SAS) Tech Organization is looking for an Applied Scientist Applied Scientist who can autonomously drive scientific innovations from research to production, developing sophisticated AI solutions that serve both Amazon's global seller base and internal Marketplace Consultants. Working in a highly collaborative environment, you'll leverage expertise in machine learning, operations research, and statistics to translate theoretical advances in LLMs, probabilistic modeling, and optimization into practical applications. The role demands strong capabilities in prototyping and iterative improvement, bridging cutting models with real-world applications while maintaining scientific rigor and measurable business impact.<br>
<br>
Key job responsibilities<br>
<ul><li>Lead the development of sophisticated AI solutions leveraging deep learning, LLMs, and advanced machine learning techniques to transform both seller operations and internal consultancy capabilities at scale</li><li>Define and drive long-term scientific vision for the organization, translating complex business challenges into innovative technical solutions that advance the state-of-the-art in applied machine learning</li></ul>
- Design and implement advanced ML architectures combining multiple learning paradigms - from reinforcement learning and causal inference to predictive modeling - to tackle critical marketplace challenges<br>
<ul><li>Architect next-generation recommendation and optimization systems that handle complex multi-dimensional constraints while maintaining robustness and interpretability at scale</li><li>Drive end-to-end development of AI applications from research through production, collaborating with engineering teams to ensure successful deployment and conducting rigorous A/B experiments to validate impact</li><li>Pioneer novel applications of foundation models and generative AI, developing sophisticated evaluation frameworks while maintaining Amazon's high standards for accuracy and reliability</li><li>Lead technical discussions across organizational boundaries, effectively communicating complex scientific concepts to diverse stakeholders while staying at the forefront of ML/AI research advancements</li></ul><br>
About the team<br>
What is Amazon Strategic Account Services (SAS)?<br>
The SAS team aims to accelerate the full potential of our Sellers, helping them to navigate the increasing complexity of the e-commerce space. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and a Customer-focused approach to achieve commercial goals of Amazon Sellers.
</div><h2 class="jobSectionHeader"><b>BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or a Master's degree and experience in building models for business application</li><li>Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Track record of investigating, designing, and delivering innovative ML solutions that drive significant business impact</li></ul><br>
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.<br>
<br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner.</div>

Applied Scientist II, Strategic Account Services (SAS)

<div><p><b>YOU ARE</b></p><p>
As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes.</p><p></p><p>
Your spans the full solution lifecycle &mdash; assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems.</p><p></p><p><b>
THE WORK</b></p><ul><li>
Formulate real-world problems into practical, efficient, and scalable AI and Machine Learning solutions</li><li>
Develop and implement machine learning algorithms, models, and computational systems; design and build scalable data pipelines to support model training and production with DevOps &amp; MLOps</li><li>
Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC</li><li>
Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites</li><li>
Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production</li><li>
Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools</li><li>
Justify the value of model approaches in business problems</li><li>
Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production</li></ul></div>
<br>
<div><p><b>EDUCATION</b></p><ul><li>
Bachelor's Degree or equivalent</li></ul><p><b>
BASIC (REQUIRED) QUALIFICATION</b></p><ul><li>
Experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing.</li><li>
Experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming</li><li>
Experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks</li><li>
Experience in building and deploying AI/ML based software to a cloud environment.</li></ul><p><b>
PREFERRED QUALIFICATION</b></p><ul><li>
Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch)..</li><li>
Experience working with language models like LLM's APIs and optimizing their usage for specific applications.</li><li>
Experience with the following programming languages: Python, C++, Java, R, SQL</li><li>
Strong written &amp; verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders</li><li>
Strong client-facing skillsets in a consulting environment</li><li>
Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams</li><li>
Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation</li><li>
MS or PhD in related field preferred (computer science, engineering, etc.)</li></ul></div>

AI/ML Computational Science Assoc Manager

Prima

<div><p>Are you looking for a new challenge?</p>
<p>
Fancy helping us shape the future of motor insurance?</p>
<p>
Prima could be the place for you.</p>
<p>
Since 2015, we&rsquo;ve been using our love of data and tech to rethink motor insurance and bring drivers a great experience at a great price. Our story began in Italy, where we&rsquo;ve quickly become the number one online motor insurance provider. In fact, we&rsquo;re trusted by over 5 million drivers. And now we&rsquo;re expanding to help millions more drivers in the UK and Spain.<br>
</p><div></div><br>
<div>To help fuel that growth, we&rsquo;re looking for Data Scientists to join our Pricing &amp; Underwriting Department, the strategic engine behind Prima's growth.</div>
<div></div>
<div>As part of this global team, you&rsquo;ll play a pivotal role in shaping our strategy and strengthening our competitive edge. Using data, analytical thinking, machine learning and business acumen, you&rsquo;ll help predict the future and set the right prices, keeping our offering both attractive and sustainable. You&rsquo;ll work with your data science tools and skills to bring real-world impact, collaborating with cross-functional teams to turn insights into action and fuel innovation across the company and its different branches.</div>
<div></div>
<h3 class="jobSectionHeader"><b>Excited to make an impact? Here are the details.</b></h3>
<h3 class="jobSectionHeader"><b>What you&rsquo;ll do</b></h3><div>
<ul><li>Leverage data to identify risks, opportunities and key pricing drivers, turning complex information into actionable insights that influence strategic decision making;</li>
<li>Leverage Machine Learning and advanced analytics to develop risk and pricing models that power real-time insurance pricing for millions of customers;</li>
<li>Contribute directly to the company&rsquo;s growth and long-term success through innovative modelling, experimentation and commercially impactful insights.</li>
</ul>
</div><div></div><h3 class="jobSectionHeader"><b>What we&rsquo;re looking for</b></h3><div>
<ul><li>Strong academic background in Mathematics, Physics, Engineering (Maths, Physics and Computer Science specialisations), Data Science, Computer Science or Statistics;</li>
<li>Strong quantitative, logical and analytical abilities, a solid foundation in statistics, probability and advanced analytics, and a curious, proactive and innovative mindset focused on solving complex problems;</li>
<li>Fluency in English, both spoken and written.</li>
</ul>
</div><div></div><h3 class="jobSectionHeader"><b>Nice-to-Have</b></h3><div>
<ul><li>Strong communication skills, with the ability to challenge assumptions, and drive new ideas;</li>
<li>Possess a solid foundation in code development and machine learning, ideally in Python;</li>
<li>Know how to create, manipulate and analyse large datasets.</li>
</ul>
</div><div></div><div><b>Please note:</b> this is the same position as the one referred as &ldquo;Data Scientist&rdquo; on our career site, posted with different job titles to reach STEM students and graduates who might not know a <b>Data Scientist</b> role suits them.</div>
<h3 class="jobSectionHeader"><b>Why you'll love it here</b></h3>
<p>
We want to make Prima a happy and empowering place to work. So if you decide to join us, you can expect plenty of perks.</p>
<p>
<b>Competitive compensation: </b>Benefit from competitive salaries, starting from &pound;80k up to &pound;160k, with clear opportunities to grow as you do.</p>
<p><b>
Work Your Way:</b> Enjoy full flexibility &ndash; work from home, the office or a mix of both. Plus, work from anywhere for up to 30 days a year.</p><div></div><p><b><br>
\uD83C\uDFC1 Grow with us:</b> We may move fast at Prima, but we move together. Get access to learning resources, mentorship and a growth plan tailored to you.</p>
<p><b>
\uD83C\uDF08 Thrive and perform:</b> Your best work begins when you feel your best. Enjoy private healthcare, gym discounts, wellbeing programs and mental health support.</p>
<p>
Think you&rsquo;re a match? Apply now.</p><br>
<p></p>
<p>
At Prima, we celebrate uniqueness. If you don&rsquo;t meet every requirement but are passionate about this role, we still want to hear from you. Innovation thrives on diverse perspectives.</p>
<p><i>
Prima is proud to be an equal opportunity employer. Need accommodations during the process? Email us at accessible.recruiting@prima.it. Let&rsquo;s build the future of insurance, together.</i></p></div>

Quantitative Analyst (Math, Physics & Engineering degrees)

iwoca

<div>
 Data Scientist - Acquisition Technology
 <br/>
 <br/>
 Hybrid in London, United Kingdom
 <br/>
 <br/>
 <strong>
  The Company
  <br/>
  <br/>
 </strong>
 Small businesses move fast. Opportunities often don&rsquo;t wait, and cash flow pressures can appear overnight. To keep going, and growing, SMEs need finance that&rsquo;s as flexible and responsive as they are.
 <br/>
 <br/>
 That's why we built iwoca. Our smart technology, data science and five-star customer service ensures business owners can act with the speed, confidence and control they need, exactly when it's needed.
 <br/>
 <br/>
 We&rsquo;ve already cleared the way for 100,000 businesses with more than &pound;4 billion in funding. Our passionate team is driven to help even more SMEs succeed, through access to better finance and other services that make running a business easier. Our ultimate mission is to support one million SMEs in their defining moments, creating lasting impact for the communities and economies they drive.
 <br/>
 <br/>
 <strong>
  The function
  <br/>
  <br/>
 </strong>
 iwoca's Data Scientists specialise in supervised machine learning, statistical inference and exploratory data analysis, focusing on tabular and time series data. Our work emphasises quantitative predictions through the analysis of conditional probabilities and expectations, using medium-sized datasets.
 <br/>
 <br/>
 <strong>
  The team
  <br/>
  <br/>
 </strong>
 The DE Acquisition Tech team sits at the heart of iwoca&rsquo;s growth strategy. Its mission is to help Marketing and Sales reach and engage small businesses of every kind, showing how our finance can empower their ambitions. The team enables smarter, data-driven decision-making across paid and organic channels as well as direct sales. By embedding engineers, product managers, designers, and data scientists together, the team acts as a self-sufficient unit, shaping strategies that deliver measurable commercial impact.
 <br/>
 <br/>
 <strong>
  The role
  <br/>
  <br/>
 </strong>
 As a Data Scientist in the DE Acquisition Tech team, you&rsquo;ll shape how iwoca grows. You&rsquo;ll design and evaluate experiments, build statistical and predictive models, and turn complex data into clear insights. You&rsquo;ll own projects end to end while working closely with stakeholders to align your work with business goals. The models and insights you deliver will directly influence how we invest in sales and marketing, giving you visibility across the company and impact on customer acquisition.
 <br/>
 <br/>
 <strong>
  The projects
  <br/>
  <br/>
 </strong>
 You&rsquo;ll shape projects that:
 <br/>
 <br/>
 <ul>
  <li>
   Run controlled experiments across paid and organic channels, generating evidence on what drives conversions.
  </li>
  <li>
   Build and refine frameworks for Paid Search and Paid Social, enabling smarter bidding and more effective performance.
  </li>
  <li>
   Develop statistical attribution models to give clear insight into channel impact.
  </li>
  <li>
   Design predictive lead scoring models that help target valuable prospects more effectively.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  The Requirements
  <br/>
  <br/>
 </strong>
 Essential:
 <br/>
 <br/>
 <ul>
  <li>
   Expertise in probability and statistics, gained through a quantitative field such as Mathematics, Physics, Statistics or similar.
  </li>
  <li>
   Ability to understand business context and translate data into actionable insights that guide decisions.
  </li>
  <li>
   Proficiency with data manipulation and modelling tools such as pandas, statsmodels or R.
  </li>
  <li>
   Experience with scientific computing tools such as NumPy, SciPy, R, Matlab, Mathematica or BLAS.
  </li>
  <li>
   Ability to work autonomously and manage projects end to end, from framing the question to delivering outcomes.
  </li>
  <li>
   Ability to communicate clearly in writing and speech, adapting technical detail to suit different audiences.
  </li>
  <li>
   A commitment to using modern tools effectively &ndash; including AI &ndash; to maximise quality, speed, and rigour, while retaining responsibility for accuracy and outcomes.
   <br/>
   <br/>
  </li>
 </ul>
 Bonus:
 <br/>
 <br/>
 <ul>
  <li>
   Understanding of Bayesian statistics, including experience or interest in applying hierarchical Bayesian models.
  </li>
  <li>
   Experience building machine learning models from scratch, including creating custom optimisers.
  </li>
  <li>
   Knowledge of stochastic processes and related mathematical techniques.
  </li>
  <li>
   Experience working with Python, our primary programming language.
  </li>
  <li>
   Understanding of financial concepts such as deterministic cash flows.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  The salary
  <br/>
  <br/>
 </strong>
 We expect to pay from &pound;60,000 - &pound;90,000 for this role. But, we&rsquo;re open-minded, so definitely include your salary goals with your application. We routinely benchmark salaries against market rates, and run quarterly performance reviews.
 <br/>
 <br/>
 <strong>
  The culture
  <br/>
  <br/>
 </strong>
 At iwoca, we prioritise a culture of learning, growth, and support, and invest in the development of our team members. We value thought and skill diversity, and encourage people to explore new areas of interest, adopt better tools (including AI), and apply sound judgement so our products and decisions improve over time.
 <br/>
 <br/>
 <strong>
  The offices
  <br/>
  <br/>
 </strong>
 We put a lot of effort into making iwoca a great place to work:
 <br/>
 <br/>
 <ul>
  <li>
   Offices in London, Leeds, Berlin, and Frankfurt with plenty of drinks and snacks.
  </li>
  <li>
   Events and community-led groups, including running groups, padel, and monthly ping-pong and pool competitions.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  The Benefits
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Flexible working hours.
  </li>
  <li>
   Medical insurance from Vitality, including discounted gym membership.
  </li>
  <li>
   A private GP service (separate from Vitality) for you, your partner, and your dependents.
  </li>
  <li>
   25 days&rsquo; holiday per year, an extra day off for your birthday, the option to buy or sell an additional five days of annual leave, and unlimited unpaid leave.
  </li>
  <li>
   A one-month, fully paid sabbatical after four years.
  </li>
  <li>
   Instant access to external counselling and therapy sessions for team members that need emotional or mental health support.
  </li>
  <li>
   3% Pension contributions on total earnings.
  </li>
  <li>
   An employee equity incentive scheme.
  </li>
  <li>
   Generous parental leave and a nursery tax benefit scheme to help you save money.
  </li>
  <li>
   Electric car scheme and cycle to work scheme.
  </li>
  <li>
   Two company retreats a year: we&rsquo;ve been to France, Italy, Spain, and further afield.
   <br/>
   <br/>
  </li>
 </ul>
 And to make sure we all keep learning, we offer:
 <br/>
 <br/>
 <ul>
  <li>
   A learning and development budget for everyone.
  </li>
  <li>
   Company-wide talks with internal and external speakers.
  </li>
  <li>
   Access to learning platforms like Treehouse.
   <br/>
   <br/>
  </li>
 </ul>
 Useful links:
 <br/>
 <br/>
 <ul>
  <li>
   iwoca benefits &amp; policies
  </li>
  <li>
   Interview welcome pack
   <br/>
   <br/>
  </li>
 </ul>
 Compensation Range: &pound;60K - &pound;90K
</div>


Data Scientist - Acquisition Tech Team

Muzz

<div>
 <p>
  <strong>
   London, UK - Hybrid (Tue, Wed &amp; Thur in Office)
  </strong>
 </p>
 <p>
  <strong>
   &pound;80,000 - &pound;90,000 + equity
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We&rsquo;re looking for a smart and ambitious data scientist, with real entrepreneurial flair to join our team and understand our members and all the metrics that matter. Love numbers and love being commercial? This role presents an opportunity to mold the future of the data science team, explore new ideas and new technologies.
 </p>
 <p>
  <br/>
 </p>
 <p>
  Muzz is the world&rsquo;s largest Muslim dating and marriage app. We&rsquo;ve got over 15 million members and have helped more than 800,000 couples get married. We&rsquo;re on our way to become the first $1 billion Muslim tech brand - but we need your help!
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Day to day
  </strong>
 </p>
 <ul>
  <li>
   You'll be joining a dynamic data science team whose goal is to grow the company and optimize our products as we expand into new markets around the world
  </li>
  <li>
   You'll be understanding our user behaviour on the platform with a view to generating actionable insights in terms of both product and marketing
  </li>
  <li>
   You'll work closely with our product, engineering and growth teams
  </li>
  <li>
   You'll be a proactive self-starter, driving innovation with a product focus
  </li>
  <li>
   You&rsquo;ll be diving into a range of data to solve our highest impact and complex challenges
  </li>
  <li>
   You'll own and evolve the production ML systems behind our personalization and recommendations serving millions of users
  </li>
  <li>
   You'll use AI tools as a core part of how you work and help set how the wider team gets the most out of them
  </li>
  <li>
   You'll raise the bar for the team - mentoring analysts and data scientists, and helping shape our technical standards and roadmap
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   At least 5 years of experience in a Data Scientist or Machine Learning Engineer role
  </li>
  <li>
   Strong Python and SQL knowledge
  </li>
  <li>
   Strong grounding in the statistical methods behind personalization and recommendations models - e.g. embeddings, ranking, collaborative filtering
  </li>
  <li>
   Excellent written and verbal communication skills and presenting to non-technical audiences
  </li>
  <li>
   Commercial mindset with the ability to harness customer insights to optimise our marketing and products
  </li>
  <li>
   Ability to work collaboratively in cross-functional teams
  </li>
  <li>
   Passionate about solving complex and challenging data problems
  </li>
  <li>
   Experience in designing and conducting A/B experiments
  </li>
  <li>
   A proven track record of developing and owning production ML pipelines - including data processing, deployment, monitoring, retraining
  </li>
  <li>
   Demonstrated end-to-end ownership of significant ML projects - from framing the problem to shipping it, and through the messy realities of live performance, edge cases and iteration once real users hit it
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Nice to have
  </strong>
 </p>
 <ul>
  <li>
   Hands-on experience with recommender systems, with real-time or near-real-time updates and serving
  </li>
  <li>
   Experience in consumer-facing mobile-first products
  </li>
  <li>
   Experience with GCP platform - BigQuery/VertexAI
  </li>
 </ul>
 <p>
  <br/>
 </p>
</div>


Senior Data Scientist

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