Why loveholidays? At loveholidays, we’re on a missionto open the world to everyone, giving our customers’ unlimitedchoice, unmatched ease and unmissable value for their next getaway.Our team is the driving force behind our role as our customers’personal holiday expert - the smart way to get away. About the teamOur Data Science team comprises eight members, including fourSenior Data Scientists, two Data Scientists, a Machine LearningEngineer and the Head of Data Science. We specialise in variousareas such as Recommender Systems, Time Series Forecasting, DeepLearning, and Reinforcement Learning, fostering a collaborativelearning environment. Our focus is on modelling andproblem-solving, leveraging advanced machine learning techniques tocreate solutions to challenging business problems. We prioritiseclean, well-tested code with a culture of documentation andknowledge sharing. Our tech stack includes GCP, Python, GitHub,PyTorch, TensorFlow, Scikit-learn, and XGBoost. With matureinfrastructure and dedicated teams for Data Engineering, Analytics,and Platform Engineering, our Data Scientists enjoy high autonomy.We tackle interesting datasets, set up large-scale experiments, andimplement growth strategies with NO red tape. Quarterly OKRplanning ensures that priorities are clearly defined and teams arealigned on objectives. The impact you’ll have: Reporting to theHead of Data Science, the Staff Data Scientist will be a technicalleader who drives strategic initiatives and shapes the technicaldirection of the Data Science function at loveholidays. You'll be acatalyst for innovation, a mentor to junior team members, and atrusted advisor to stakeholders across the business, helping toimplement our AI strategy and align data science capabilities withbusiness objectives. Your day-to-day: - Leading strategicinitiatives from conception to delivery, including stakeholdermanagement and business value articulation - Researching anddeveloping cutting-edge models and techniques to tackle complexbusiness challenges - Establishing and implementing best practicesacross data science systems and services - Providing technicalleadership and mentorship to junior team members, facilitatingtheir growth and development - Proactively identifying andimplementing improvements to team processes or workflows -Contributing to architectural decisions for data scienceinfrastructure - Leading knowledge sharing sessions throughtechnical presentations of projects - Representing data science incross-functional initiatives and being a trusted advisor beyondyour immediate team - Participating in project prioritisation andstrategic planning for the data science function - Implementingcomprehensive monitoring solutions and designing fault-tolerantsystems Your skillset: We're seeking an exceptional technicalleader who can drive innovation while maintaining productionexcellence. The following qualities are essential: - TechnicalExcellence: Deep expertise in machine learning approaches with theability to assess and implement cutting-edge algorithms - StrategicThinking: Ability to break down high-level optimisation goals intolower-level components whilst understanding complex/second-orderconsequences - Leadership: Proven ability to mentor others, resolveconflicts, and be a key motivator for team members - BusinessAcumen: Strong ability to link technical solutions to businessoutcomes and prioritise work based on impact - Communication:Exceptional ability to translate complex technical concepts tonon-technical stakeholders and influence decision-making -Problem-Solving: Track record of resolving complex technicalchallenges that impact multiple teams - Collaboration: Demonstratedsuccess working across functions and teams to deliver high-impactprojects Required Experience - Leading multiple end-to-end projectssimultaneously, from inception through to production monitoring andoptimisation - Designing and implementing sophisticated experimentsand models that significantly enhance business performance -Expert-level knowledge of machine learning and statistical methodsfor predictive modelling and forecasting - Extensive experiencedeploying ML models to production at scale with robust monitoringsystems - Advanced knowledge of SQL and data manipulationtechniques - Mastery of software engineering best practicesincluding unit testing, CI/CD, model management and experimenttracking - Track record of successful technical mentorship and teamdevelopment - Demonstrated cross-functional collaboration skillsacross engineering, product, and business teams Desirable -Expertise in Deep Learning, Generative AI and ReinforcementLearning - Advanced knowledge of Time Series Forecasting andRecommender Systems - Previous experience working in e-commerce,retail, or the travel industry - Experience designing and analysinglarge-scale A/B test experiments - Mastery of workfloworchestration technologies such as Airflow, Dagster or Prefect -Expert knowledge of technologies such as: - Google Cloud Platform,particularly Vertex AI - Docker and Kubernetes - Infrastructure asCode - Experience establishing data science best practices acrossan organisation Perks of joining us: - Company pensioncontributions at 5%. - Individualised training budget for you tolearn on the job and level yourself up. - Discounted holidays foryou, your family and friends. - 25 days of holidays per annum (plus8 public holidays) increases by 1 day for every second year ofservice, up to a maximum 30 days per annum. - Ability to buy andsell annual leave. - Cycle to work scheme, season ticket loan andeye care vouchers. At loveholidays, we focus on developing aninclusive culture and environment that encourages personal growthand collective success. Each individual offers unique perspectivesand ideas that increase the diversity and effectiveness of ourteams. And we value the insight and potential you could bring onour continued journey. The interview journey: - TA screening withsomeone from our Talent team - 30 minutes - 1st stage interviewwith the Head of Data Science - 45 minutes - Panel interview withkey stakeholders, including a task to present in office - 1.5 hours- Final stage with Chief Data Officer - 45 minutes#J-18808-Ljbffr
