lead data scientist

Altak Group Inc.

<div>
 
 
 Job Title: Lead Data Scientist &ndash; Healthcare (AI Architecture Focus)
 
 
 
 
 Location: EAST coast (REMOTE)
 
 
 
 
 
 
 
 Required Qualifications
 
 
 
 &bull; 7+ years of experience in data science, with recent experience in a Lead Data
 
 
 Scientist or similar senior role.
 
 
 &bull; Strong experience working in the healthcare domain (payer, provider, life
 
 
 sciences, digital health, or health tech).
 
 
 &bull; Hands-on experience designing and deploying ML models in production
 
 
 environments.
 
 
 &bull; Solid understanding of AI architecture concepts, including scalable ML
 
 
 systems, MLOps, and cloud-based deployments.
 
 
 &bull; Proficiency in Python and common ML libraries (e.g., scikit-learn, TensorFlow,
 
 
 PyTorch).
 
 
 &bull; Experience with SQL and big data technologies (e.g., Spark, Databricks,
 
 
 Snowflake).
 
 
 &bull; Strong understanding of data modeling, statistics, and machine learning
 
 
 algorithms.
 
 
 &bull; Experience working in cloud environments such as AWS, Azure, or GCP.
 
 
 &bull; Excellent communication skills with the ability to explain complex technical
 
 
 concepts to non-technical stakeholders.
 
 
 
 
 
 
 
 
 
 Preferred Qualifications
 
 
 
 &bull; Prior experience collaborating closely with or acting as an AI Architect on
 
 
 enterprise-scale solutions.
 
 
 &bull; Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow,
 
 
 SageMaker, Azure ML).
 
 
 &bull; Familiarity with NLP, computer vision, or generative AI use cases in healthcare.
 
 
 &bull; Knowledge of healthcare interoperability standards such as HL7, FHIR, or ICD
 
 
 codes.
 
 
 &bull; Experience leading cross-functional teams in a contract or consulting
 
 
 environment.
 
</div>

Lead Data Scientist

1st Central

<div>
 
 
 At 1st Central, everything starts with our people.
 
 
 
 
 
 
 As one of the UK&rsquo;s leading motor and home insurers, we use smart technology, data and great service to make insurance fast, fair and simple for over 1.4 million customers. We&rsquo;re proud to create an environment where people feel supported, trusted and able to grow - whether that&rsquo;s developing new skills, taking on fresh challenges or making a real impact every day. If you&rsquo;re looking for a role where you can make a difference, we&rsquo;d love to hear from you.
 
 
 
 
 
 We&rsquo;re looking for a
 
 Lead Data Scientist
 
 to join a team of data scientists and specialists, helping to deliver a portfolio of innovative services that unlock value from the company&rsquo;s extensive information assets. In this role, you&rsquo;ll apply advanced data science techniques, both independently and collaboratively, to uncover insights and drive business value. As a senior member of the team, you&rsquo;ll also play a key role in mentoring and upskilling colleagues.
 
 
 
 
 
 You&rsquo;ll work with large volumes of data from a variety of sources, including structured and unstructured datasets. Using strong critical thinking and problem-solving skills, you&rsquo;ll analyse and interpret data, build predictive models, and develop machine learning algorithms to generate actionable insights.
 
 
 
 
 
 As the Lead Data Scientist, you&rsquo;ll be responsible for proposing solutions to business challenges and partnering with cross-functional teams to implement them. Recognising the dependencies Group companies have on technology provided in-house, you&rsquo;ll collaborate closely with in-house technology providers, as well as data presentation and delivery teams across multiple locations, to ensure seamless and effective outcomes.
 
 
 
 
 
 We&rsquo;re big on
 
 flexible hybrid working
 
 . Our teams are based across
 
 Haywards Heath (West Sussex)
 
 and
 
 Salford Quays (Manchester).
 
 We primarily work from home but value collaboration, so we come together in person to keep ideas flowing, typically once a quarter. Prefer being in the office more often? That works for us too.
 
 
 
 
 
 
 Core skills we&rsquo;re looking for to succeed in the role:
 
 
 
 
 
 <ul>
 <li>
 
 Analytical &amp; Technical Skills:
 
 Proven analytical and statistical modelling skills
 </li>
 <li>
 
 Technical Skills:
 
 Familiarity with data science tools and programming languages (e.g.
 
 Python
 
 )
 </li>
 <li>
 
 Machine Learning:
 
 Ability to build and train Machine Learning models
 </li>
 <li>
 
 Professional Experience:
 
 Current Data Science experience, with
 
 Insurance
 
 industry exposure, highly advantageous
 </li>
 <li>
 
 Organisation &amp; Time Management:
 
 Strong time-management and organisational skills
 </li>
 <li>
 
 Education &amp; Qualifications:
 
 Degree in Data Science or other quantitative field
 </li>
 <li>
 
 Communication &amp; Stakeholder Management Skills:
 
 Strong verbal and written communication skills, with proven experience engaging and influencing stakeholders at all levels.
 </li>
 </ul>
 
 
 
 
 Why not check out the full job profile on our career pages and apply today
 
</div>

Smarsh

<div><div>Who are we?</div><div></div><div> 
Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines. Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.</div><div></div><div> 
Summary</div>
<div></div>
<div>As a Lead Data Scientist (NLP &amp; Financial Compliance) at Smarsh, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You&rsquo;ll work on highly specialized problems at the intersection of natural language processing, communications intelligence, financial supervision, and regulatory compliance, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk.</div>
<div></div>
<div>The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both technical excellence in NLP modeling and a deep understanding of financial domain behavior&mdash;including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.</div>
<div></div>
<div>This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.</div>
<h3 class="jobSectionHeader">How will you contribute?</h3><ul>
<li>Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.</li>
<li>Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication).</li>
<li>Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities</li>
<li>Data annotation and quality review</li>
<li>Exploratory data analysis and model fail state analysis</li>
<li>Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.</li>
<li>Client/prospect guidance in machine learning model and analytic fine-tuning/development processes</li>
<li>Provide guidance to junior team members on model development and EDA</li>
<li>Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team&rsquo;s tooling, technique and procedures</li>
<li>Continued self-led personal development</li>
</ul><h3 class="jobSectionHeader">What will you bring?</h3><ul>
<li>Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology</li>
<li>Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse</li>
<li>Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc&hellip;)</li>
<li>Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)</li>
<li>Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc&hellip;)</li>
<li>Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)</li>
<li>Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo</li>
<li>Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes</li>
<li>Familiarity with Deep Learning techniques for NLP.</li>
<li>Familiarity with LLMs - using ollama &amp; Langchain</li>
<li>Excellent verbal and written skills</li>
<li>Proven collaborator, thriving on teamwork</li>
</ul>
<div></div><div>Preferred Qualifications</div>
<ul><li>Master&rsquo;s or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field</li>
<li>Familiarity with cloud computing platforms (AWS, GCS, Azure)</li>
<li>Experience with automated supervision/surveillance/compliance tools</li>
</ul><div></div>
<div>The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.</div>
<div></div>
<div>The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.</div>
<div></div>
<div>Local cost of living assessments are done for each new hire at the time of offer.</div><div>
About our culture</div><div></div><div> 
Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world&rsquo;s leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.</div></div>

bet365

<div>Company Description 
We&rsquo;re one of the world&rsquo;s leading online gambling companies, revolutionising the industry since 2000. Founded by Denise Coates CBE, we now employ over 10,000 people and serve over 120 million customers in 26 languages.
We empower our employees to push boundaries and explore new ideas, cultivating a culture that celebrates and rewards creativity. This offers employees a wealth of growth opportunities, giving them the opportunity to make a real impact in the world of online gambling. As a forward-thinking company, we&rsquo;re breaking new ground in software innovation too, redefining what&rsquo;s possible for our global worldwide.
Our focus on In-Play betting has solidified our market-leading position, featuring more than 1.38 million In-Play sporting events a year. With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else in Europe (750,000), we handle over 6 million HTTP requests daily and process more than 1.5 million bets per hour at peak. 
Job Description 
As a Lead Data Scientist, you will spearhead the development of advanced probabilistic models that power real-time betting markets.
The Quantitative Analysis department harnesses data-driven insights to enhance our betting products and services. The team is responsible for designing, developing, and maintaining sophisticated mathematical models to provide accurate pricing across our sports betting products.
In this role, you will work with extensive datasets develop models that determine odds and power in-play betting decisions while leveraging state-of-the-art machine learning techniques to analyse and interpret complex sports data. Our fast-paced, delivery-focused environment offers significant opportunities for technical growth and innovation.
This role is eligible for inclusion in the Company's hybrid working policy. 
Qualifications 
<ul><li>
Ability to leverage in-depth knowledge of sports and online gambling to develop relevant, impactful models aligned with business objectives.</li><li>
Master&rsquo;s degree or PhD in Mathematics, Data Science, Computer Science, or a related quantitative field.</li><li>
Proven success in leading the design, development, and deployment of sophisticated predictive models.</li><li>
Expertise in Python/R and ML frameworks, such as scikit-learn, TensorFlow, or PyTorch,</li><li>
Proven ability to design and implement complex machine learning solutions and guiding best practice.</li><li>
Deep understanding of statistical analysis and probability theory.</li><li>
Demonstrable experience overseeing the implementation of highly accurate, computationally efficient, and scalable models for large-scale production environments.</li><li>
Track record of mentoring junior colleagues and successfully leading technical projects.</li><li>
Experience with cloud computing environments for scalable solutions.</li></ul> 

Additional Information 
<ul><li>
Leading the development and implementation of innovative data solutions for complex challenges, solving problems without prescriptive approaches.</li><li>
Overseeing advanced analysis of large datasets to derive actionable insights aligned with business objectives.</li><li>
Developing predictive models and algorithms using statistical techniques and machine learning.</li><li>
Conducting and supervising rigorous statistical validation of models against historical and live data.</li><li>
Collaborating with trading teams to incorporate domain expertise into mathematical models.</li><li>
Partnering with software architects and developers to ensure alignment with technical solutions.</li><li>
Optimising model performance for both accuracy and computational efficiency.</li><li>
Researching and implementing novel approaches from academic literature and industry advancements.</li><li>
Mentoring less experienced team members, providing guidance, and conducting quality assurance to enhance overall team performance and capabilities.</li><li>
Identifying and defining new opportunities for data-driven insights.</li></ul><div></div>
By applying to us you are agreeing to share your Personal Data in accordance with our Recruitment Privacy Notice - https://www.bet365careers.com/privacy-policy

At bet365, we're committed to creating an environment where everyone feels welcome, respected and valued. Where all individuals can grow and develop, regardless of their background. We're Never Ordinary, and we're always striving to be better. If you need any adjustments or accommodations to the recruitment process, at either application or interview, please don&rsquo;t hesitate to reach out.</div>

Lead Data Scientist, Sports

Motiva Enterprises LLC

<div>At Motiva, our employees&rsquo; energy, passion, and dedication to excellence are what make us who we are and what allows us to generate energy that makes a house a home, gets us from point A to point B, and enables our health and wellbeing. We invest in every aspect of our employees&rsquo; lives because, at Motiva, our people matter.
Headquartered in Houston, Texas, Motiva refines, distributes and markets petroleum products throughout the Americas. The company&rsquo;s Port Arthur Manufacturing Complex in Port Arthur, TX, is comprised of North America&rsquo;s largest refinery with a total throughput of 720,000 barrels per day, the largest base oil plant in the western hemisphere, and an integrated chemical plant. Under exclusive long-term brand licenses with Shell and Phillips 66 (for the 76&reg; brand), Motiva&rsquo;s commercial operations supply more than 12 billion gallons of fuel to customers annually. Motiva is wholly owned by Aramco, one of the world&rsquo;s largest integrated energy and chemicals companies.
Position Overview:
We are seeking a highly skilled Lead Data Scientist, Data &amp; Analytics with deep expertise in enterprise data modeling, data warehousing, and analytics platform engineering. This role will be responsible for designing, building, and optimizing scalable data solutions that support enterprise reporting, advanced analytics, and AI initiatives. The ideal candidate combines strong data engineering capabilities with extensive experience in logical and physical data modeling, dimensional modeling, and schema optimization. This individual will play a key role in establishing trusted, high-performance data foundations that enable reporting, self-service analytics, and AI-driven decision-making across the organization.
This role is a Houston-based, in-office position at Motiva&rsquo;s corporate headquarters in downtown Houston, TX.
Responsibilities<ul><li>
Design and maintain conceptual, logical, and physical data models, including Entity Relationship Diagrams (ERDs), to support enterprise data initiatives.</li><li>
Lead the design and implementation of scalable dimensional models using Star and Snowflake schemas for reporting and analytics workloads.</li><li>
Design new data schemas and optimize existing schemas to improve performance, scalability, and usability for high-volume reporting and analytical applications.</li><li>
Establish and enforce data modeling standards, naming conventions, and best practices across the enterprise.</li><li>
Build, maintain, and optimize data pipelines using Databricks, Azure Data Factory, Databricks Lakeflow Designer.</li><li>
Optimize query performance, and storage patterns to support large-scale reporting, analytics, and AI workloads.</li><li>
Support the design of semantic layers and analytical data structures that enable enterprise KPI reporting and executive dashboards.</li></ul>
Experience and Qualifications:
Required Education and Experience:
<ul><li>Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field.</li><li>
10+ years of experience in Data Engineering, Data Warehousing, Data Architecture, or related disciplines with Medallion Architecture (Bronze, Silver, Gold).</li><li>
Extensive experience creating Logical Data Models (LDMs), Physical Data Models (PDMs), and Entity Relationship Diagrams (ERDs).</li><li>
Strong hands-on experience designing and implementing dimensional models, including Star Schema and Snowflake Schema architectures.</li><li>
Hands-on experience with Databricks, Apache Spark, Delta Lake, and modern Lakehouse architectures building scalable ETL/ELT data pipelines in cloud-based environments.</li><li>
Strong understanding of data warehousing principles, metadata management, and data quality frameworks.</li><li>
Experience working with large-scale enterprise datasets and complex business processes.</li></ul>
Preferred Education and Experience:
<ul><li>Experience supporting AI, machine learning, and advanced analytics use cases.</li><li>
Familiarity with Power BI, or other enterprise business intelligence tools.</li><li>
Experience implementing data governance, master data management (MDM), and data quality programs.</li><li>
Experience in downstream energy, supply chain, manufacturing, logistics, or other asset-intensive industries.</li></ul>
We reserve the right to amend or withdraw Motiva jobs at any time, including prior to the closing date. Depending on qualifications, the successful candidate may be offered a position at a more appropriate level and/or grade.
Applicants for regular U.S. positions must be authorized to work in the United States for Motiva Enterprises LLC without the need for sponsorship of an immigration authorization or visa (for example, TN, H-1B, or other employment-based immigration authorization or visa).
Motiva participates in E-Verify.
All qualified applicants will receive consideration for employment without regard to race, color, sex, national origin, age, religion, disability, sexual orientation, gender identity, protected veteran status, citizenship, genetic information, or other protected status under federal, state, or local laws.</div>

Lead Data Scientist, Data & Analytics

Vinted

<div>
 
 Brief Info About Vinted
 
 
 
 Our mission is to make second-hand the first choice, and we're looking for people who want to help us get there. Every day, we work together to help our members buy and sell pre-loved clothing and lifestyle items, giving each piece a second life &ndash; or even a third.
 
 
 The Vinted Group is made up of three business units that support this mission:
 
 
 
 Vinted Marketplace
 
 is Europe&rsquo;s leading platform for second-hand fashion and a go-to destination for all kinds of pre-loved items, with a growing range of categories. Our platform connects millions of members across 20+ markets, helping great items find a new life.
 
 
 
 Vinted Go
 
 enhances the shipping experience with a vast network of over 500,000 pick-up and drop-off points, partnering with more than 60 carriers across Europe, with added services like item verification for peace of mind on high-value pieces.
 
 
 
 Vinted Pay
 
 is the newest part of the Vinted Group, dedicated to bringing secure, reliable payments to buyers and sellers across Europe. Seamlessly integrated into the Vinted app, it helps keep every transaction safe, efficient, and easy for our members.
 
 
 Founded in 2008 in Lithuania, Vinted began as a way for friends to find new homes for clothes they no longer needed. In 2019, we became Lithuania's first unicorn! Today, our headquarters remain in Vilnius, and we've grown with offices across Europe, supported by a team of over 2,000 people.
 
 
 
 Information About The Position
 
 
 
 Vinted&rsquo;s Revenue domain is growing &mdash; Ads business is on the mission to develop an advertising ecosystem within Vinted and we&rsquo;re just getting started. We&rsquo;re looking for a Lead Data Scientist to join our cross-functional team in Ads to help us make the most of our real estate and evolve toward a high‑performance, privacy‑respectful, in‑house advertising ecosystem over time. Think: an ad of an external partner can generate euros directly but we may well advertise our own Marketplace services or newly launched categories to optimise on net revenue as well as user engagement.
 
 
 If you have built performance-first Ad optimisation systems and are ready to take on hands-on work while shaping the Data Science roadmaps from a greenfield state - this role is for you.
 
 
 
 In this position, you&rsquo;ll
 
 
 
 <ul>
 <li>
 Own optimization logic for Ads systems. Own the data science approach behind core Ads optimization problems such as ranking, targeting, pacing, budget allocation, candidate selection, and auction or bidding logic where relevant.
 </li>
 <li>
 Develop practical approaches that improve advertiser performance, marketplace relevance, and business outcomes.
 </li>
 <li>
 Take charge of model and algorithm development. Design, develop, and iterate models and algorithmic approaches used in Ads delivery and optimization. This may include prediction, scoring, calibration, exploration/exploitation methods, and constrained optimization approaches suited to Vinted&rsquo;s marketplace context.
 </li>
 <li>
 Lead experimentation and performance improvement frameworks. Own the analytical and experimental process for improving optimization systems. Define hypotheses, evaluation frameworks or logic changes and support translating learnings into better system behavior.
 </li>
 <li>
 Guide objective function and constraint design. Help define optimization objectives that balance advertiser value, revenue, user experience, and operational constraints. Turn product and business goals into tractable optimization problems and implementable Data Science logic.
 </li>
 <li>
 Be responsible for Ads performance diagnostics. Own deep-dive analysis of system behavior and performance degradation. Identify where delivery, relevance, auction dynamics, supply-demand imbalance, or model issues are limiting outcomes, and propose solutions.
 </li>
 <li>
 Contribute to Production implementation in Ads. Partner with engineering and Decision Scientists to move models and optimization logic from idea to reliable implementation.
 </li>
 <li>
 Partner with Product Managers, Decision Scientists, Analytics Engineers and developers to shape advertiser-facing features and internal optimization capabilities with a clear understanding of feasibility, impact, and tradeoffs from the Data Science perspective.
 </li>
 <li>
 Collaborate with Decision Science counterparts and other Data Scientists to ensure optimization changes are evaluated with appropriate metrics, guardrails, and marketplace context.
 </li>
 <li>
 Partner with Analytics Engineering, Data Engineering, and backend teams to ensure training data, feedback loops, online signals, and offline datasets are suitable for robust optimization work.
 </li>
 <li>
 Help explain system behavior, performance drivers, and expected impacts of optimization changes to non-technical stakeholders when needed.
 
 
 </li>
 </ul>
 
 About You
 
 
 
 We are looking for someone who combines:
 
 
 <ul>
 <li>
 strong applied machine learning and statistical skills,
 </li>
 <li>
 experience with Ad Tech systems and optimization problems,
 </li>
 <li>
 strong product and business judgment,
 </li>
 <li>
 comfort working on production systems with engineers,
 </li>
 <li>
 and the ability to operate effectively in ambiguous, evolving domains.
 
 
 </li>
 </ul>
 The strongest candidates will have experience in areas such as:
 
 
 <ul>
 <li>
 ads ranking,
 </li>
 <li>
 auction systems,
 </li>
 <li>
 pacing and budget optimization,
 </li>
 <li>
 marketplace or recommendation systems,
 </li>
 <li>
 relevance modeling,
 </li>
 <li>
 or other real-time optimization environments where multiple objectives must be balanced.
 </li>
 <li>
 Well-versed in Python and SQL, BigQuery is an advantage
 </li>
 <li>
 Have a structured, meticulous way of working when trying out different approaches towards a set goal
 </li>
 <li>
 Be a conscious team player who understands when their work touches that of other team members and proactively aligns with them
 </li>
 <li>
 Good at explaining details of machine learning methods to lay audiences
 </li>
 <li>
 Solid written and spoken English
 
 
 </li>
 </ul>
 
 Studies show that women and members of underrepresented communities often apply for jobs only if they meet 100% of the qualifications. If you don&rsquo;t recognise yourself in all of the above, you might still be an excellent candidate for this position. If this role excites you, we encourage you to apply.
 
 
 
 
 Work perks
 
 
 
 <ul>
 <li>
 The opportunity to benefit from our share options programme
 </li>
 <li>
 25 days of paid annual leave
 </li>
 <li>
 Newest MacBook models
 </li>
 <li>
 Digital mental and emotional health support and Employee Assistant Program (EAP)
 </li>
 <li>
 Frequent team-building events
 </li>
 <li>
 Home office support: we provide IT workstation equipment and a personal budget of up to &euro;540 for home workplace furniture
 </li>
 <li>
 Lunch benefit per working day
 </li>
 <li>
 Access to a discounted gym membership plan
 </li>
 <li>
 A personal monthly budget for shopping on Vinted
 </li>
 <li>
 Collective Defined Contribution Pension plan
 </li>
 <li>
 NS Business Card for your commute to the office by public transport
 </li>
 <li>
 The opportunity to spend up to 90 days per year - 21 of which can be spent working outside of the EU - on workation
 </li>
 <li>
 A dog-friendly office
 
 
 </li>
 </ul>
 
 Working at Vinted
 
 
 
 
 Individual Learning Budget
 
 
 
 We invest in your professional growth! As part of our commitment to continuous learning, we offer an annual learning budget to support your personal and career development through courses, certifications, workshops and more.
 
 
 
 Hybrid Work
 
 
 
 We&rsquo;ve adopted a hybrid workplace model where 2 days in the office are recommended but not enforced. It&rsquo;s up to you and your team to decide on the exact days you&rsquo;ll spend working together in person.
 
 
 
 Equal Opportunity
 
 
 
 The Vinted Group is committed to building an inclusive workplace where people from all walks of life feel a sense of belonging. We welcome applications from people of all backgrounds, identities and life experiences. At Vinted, all applicants are treated fairly without regard to their race, age, religion or belief, sex, national origin, citizenship, gender identity, sexual orientation, disability, or any other protected characteristic.
 
 
 The annual gross salary range for this position is:
 
 
 &euro;86.600&mdash;&euro;127.400 EUR
</div>

Lead Data Scientist, Revenue - Ads, Revenue

Talan

<div>Company Description 
Talan Data x AI is a leading Data Management and Analytics consultancy, working closely with leading software vendors and top industry experts across a range of sectors, unlocking value and insight from their data. At Talan Data x AI, innovation is at the heart of our client offerings, and we help companies to further improve their efficiency with modern processes and technologies, such as Machine Learning (ML) and Artificial Intelligence (AI). 
Job Description 
We are hiring a Lead Data Scientist to drive the technical delivery of our most demanding AI engagements and to lead a growing team of data scientists and AI engineers. This role is for a practitioner who is equally fluent in the rigour of traditional data science (statistical modelling, machine learning, experimentation) and the fast-moving world of large language models and agentic AI. You understand that the best solutions often combine both.
You will own delivery from problem framing through to deployment, ensuring the work is technically sound, commercially valuable, and aligned to the architectural vision. As a lead, you will mentor the team, raise engineering and modelling standards, and act as a trusted technical partner in client conversations. You will help clients see not just what is possible, but what is practical and worth doing.
This is a delivery-focused leadership role with genuine breadth: one week you might be tuning a forecasting model, the next designing an agentic workflow or evaluating an LLM pipeline for a client pilot.
Required skills &amp; experience:<ul><li>
Lead end-to-end delivery of data science and AI projects, owning technical quality and outcomes.</li><li>
Combine classical ML (regression, classification, forecasting, optimisation) with modern GenAI, LLM, and agent-based approaches as the problem demands.</li><li>
Mentor and develop data scientists, AI engineers, and junior consultants, growing the team's capability.</li><li>
Translate business problems into well-scoped analytical and AI solutions and communicate results to non-technical stakeholders.</li><li>
Ensure best practice across the AI lifecycle &mdash; experimentation, evaluation, testing, deployment, and monitoring.</li><li>
Act as the bridge between architecture and delivery, ensuring implementation stays faithful to design.</li><li>
Support pre-sales and client discussions with credible technical input and realistic estimation.</li><li>
Champion reproducibility, model governance, and responsible practice in everyday delivery.</li></ul> 

Qualifications 
To qualify for this role, you must have:
<ul><li>Minimum 5 years in data science or AI delivery, including hands-on leadership of technical teams or workstreams.</li><li>
Strong foundations in machine learning and statistics, with demonstrable production experience.</li><li>
Practical experience with LLMs and generative AI &mdash; prompting, RAG, fine-tuning, and evaluation.</li><li>
Exposure to AI agents and orchestration frameworks, and an appetite to deepen it.</li><li>
Proficiency in Python and the modern data / ML stack; sound data engineering instincts.</li><li>
Excellent communication and stakeholder skills, ideally in client-facing or consulting settings.</li></ul>
Ideally, you&rsquo;ll also have, but not essential:<ul><li>
Familiarity with the Azure AI ecosystem (Azure ML, Azure OpenAI, Databricks / Fabric).</li><li>
Experience supporting business development or pre-sales.</li><li>
Domain depth in a regulated or data-rich industry.</li><li>
Contributions to open source, publications, or a visible professional profile.</li></ul>
You must be:<ul><li>
Willing to work on client sites, potentially for extended periods.</li><li>
Willing to travel for work purposes and be happy to stay away from home for extended periods.</li><li>
Eligible to work in the UK without restriction.</li></ul>
#TalanUK #LI-HB1 
Additional Information 
Compensation &amp; Benefits Package:<ul><li>
BDP Plus &ndash; A reward programme whereby you accrue points to trade against a 3-month paid sabbatical or cash equivalent.</li><li>
25 days holiday + bank holidays.</li><li>
5 days holiday buy/sell option.</li><li>
Private medical insurance.</li><li>
Life cover.</li><li>
Cycle to work scheme.</li><li>
Eligibility for company pension scheme (5% employer contribution, salary sacrifice option).</li><li>
Employee assistance programme.</li><li>
Bespoke online learning via Udemy for Business.</li></ul>
Why join:
You will lead substantive, end-to-end AI work in a practice that is scaling fast and backing its people to grow with it. You will shape how a team works, influence how clients adopt AI, and keep your own skills at the frontier, bridging proven data science with the most current GenAI and agentic techniques. It is an opportunity to lead, deliver, and keep building.</div>

Lead Data Scientist (Classical ML, LLMs & AI Agents)

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Lead Data Scientist (Classical ML, LLMs & AI Agents)