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This role will work cross-functionally with product, insights, analytics, marketing, and finance. Ideal candidates thrive in fast-paced environments and have a proven ability to translate data into business outcomes. Know where you belong. Match Group is a leading provider of dating services across the globe. Our portfolio includes Tinder, Match, Hinge, PlentyOfFish, The League, and others, each designed to spark meaningful connections for singles worldwide. Creating a sense of belonging doesn't stop at our platforms\u2014it's the foundation of every team we hire. When it comes to dating, the connection starts online, but the real magic happens once you meet in real life (IRL). We think the same is true for creating the best platforms, so we work together IRL in our New York office 3 days/week. How You'll Make an Impact: Lead the development of integrated data-backed media strategies across all channels (digital, social, traditional, and emerging platforms) to drive user acquisition, brand growth, and review across Match Group Build and present business case for new initiatives; including risk and opportunities Partner with brand, creative, insights and analytics teams to align media strategies with overall business goals, setting clear expectations for outcomes Use data-driven insights to guide media mix decisions, audience segmentation, and campaign optimization. Stay ahead of media trends, technologies, and platform updates to drive innovation and competitive advantage. Collaborate with cross-functional teams (brand, comms, product marketing, analytics) to ensure cohesive storytelling and channel alignment. Partner with shared media buying team and agencies to effectively communicate and implement campaigns Serve as the knowledge export for all media channels We Could Be a Match If You Have: 5+ years in strategy, consulting, growth marketing, or media in a consumer tech or subscription-based company. Rich knowledge of the ever changing media landscape; domestic required, international preferred Exceptional analytical skills with the ability to show how media plans will impact business outcomes Strong collaboration and communication skills; comfortable presenting to senior stakeholders. Experience with performance marketing, brand media, and emerging digital platforms. Bachelors degree in Business, Economics, Marketing, or related field $ 125000- $135000 a year Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of New York, NY. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting. LI- LH1 Why Match Group? Our mission is simple - to help people find love and happiness! We love our employees too and understand the importance of all life's milestones. Here are some of the benefits we are proud to offer: Mind & Body - Medical, mental health, and wellness benefits to support your overall health and well-being Financial Wellness - Competitive compensation, 100% employer match on 401k contributions up to 10% (cap at $10,000), as well as an employee stock purchase program to help you feel supported in your financial security Unplug - Generous PTO and 14 paid holidays so you can unplug Career - Annual training allowance for professional development and ERG membership opportunities and events so you feel connected and empowered in your work Family - Families come in all shapes and sizes so we offer 20 weeks of 100% paid parental leave, fertility, adoption, and child care resources, as well as pet insurance and discounts Company Gatherings - We host fun happy hours and company events where our employees get to know each other and build a sense of connection and belonging! We are proud to be an equal opportunity employer and we value the rich dynamics that diversity brings to our company. We do not discriminate on the basis of race, religion, color, creed, national origin, ancestry, disability, marital status, age, sexual orientation, sex (including pregnancy and sexual harassment), gender identity or expression, uniformed service or veteran status, genetic information, or any other legally protected characteristic. Period. If you require a reasonable accommodation to participate in the hiring process \u2014 such as during pre-employment testing or interviews \u2014 please indicate this by selecting \u201cYes\u201d in the accommodation request field. We'll reach out to discuss your needs if you're selected for the interview stage. Match", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/39259405", "isPrivate": false}, {"id": 38636194, "name": "Sr. Director, Global Escalations", "location": "Dallas, Texas", "locations": ["Dallas, Texas"], "hot": 0, "department": "Match", "business_unit": "Care", "t_update": 1766379687, "t_create": 1761608098, "ats_job_id": "3544c2d8-0fce-4dff-94ba-ba387624f098", "display_job_id": "R0004686", "type": "ATS", "id_locale": "R0004686-en", "job_description": "Deliver best-in-class customer experience by building a quality driven culture that's obsessed with member experience and satisfaction, with both internal teams and external business partners. Support multiple brands through the development and execution of a shared service strategy, driving consistency, efficiency, and scalability across operations while tailoring solutions to the unique needs of each brand. Work closely with key stakeholders - Quality, Training, Policy, Legal, Comms, and Product, on time sensitive issues and escalations. Minimum of 10 years experience in either Trust & Safety, Customer Support Operations or a community management role at a technology company, 5+ years of management experience. Advanced knowledge of CRM tools (i.e., Zendesk) People leader with an eye toward development. Big ideas thinker and cultivator. Critical thinking skills to understand and summarize complex issues quickly. Ability to multitask, prioritize, and keep up with a large volume of tasks in a fast-paced environment. Experience with user policies, TOS, and escalation procedures in a member facing environment. Extreme attention to detail. Passion for helping people. Bachelor degree or higher.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "remote_local", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38636194", "isPrivate": false}, {"id": 38778953, "name": "Ad Operations Analyst", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Match Media", "business_unit": "Marketing", "t_update": 1766379687, "t_create": 1762755468, "ats_job_id": "7843c6e6-5699-406b-b9a8-fbdd3bc7dd3e", "display_job_id": "7843c6e6-5699-406b-b9a8-fbdd3bc7dd3e", "type": "ATS", "id_locale": "7474540297392929332-en", "job_description": "Performing all aspects of traffic management for direct campaigns, including accurate and timely set up, testing, management and optimization of online display ad and video ad campaigns in Google Ad Manager. Perform QA for all campaigns prior to going live Provide guidance to internal stakeholders regarding inventory management and best practices for ad performance Provide technical support for sales and engineering teams to help troubleshoot problem creative Develop optimization strategies on a campaign-by-campaign basis to maximize both delivery and advertiser performance Ensure smooth delivery of campaigns by maintaining and distributing pacing reports Work with product teams to implement and test new ad products/ad experiences Provide excellent customer service to internal stakeholders and external partners Establish, implement and maintain digital ad operations best practices Ability to meet deadlines and handle multiple tasks Experience with troubleshooting tools such as Charles, Proxyman etc", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "hybrid", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38778953", "isPrivate": false}, {"id": 38762858, "name": "Marketing Analytics Lead", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Marketing", "t_update": 1766379687, "t_create": 1762463945, "ats_job_id": "c4a3e371-5cb2-4877-99b8-3a3f95c0be48", "display_job_id": "R0004626", "type": "ATS", "id_locale": "R0004626-en", "job_description": "Build and maintain executive-ready dashboards/scorecards by market, objective, and channel (spend, reach, efficiency, brand health and brand lift). Set the agenda, build the pack, and facilitate the monthly discussion with the VP and Directors. Present regional, country, strategy and and channel-level trends; explain actual vs. forecast variance, drivers, risks, and opportunities. Recommend reallocation scenarios across campaigns/channels; track decision follow-through. Run \u201cwhat-if\u201d scenarios using MMM elasticities and test results to guide investment allocation. Maintain market-level forecasts; decompose variance and advise on course-corrections. Tracking of country level allocations by strategy against annual plan Prepare/share clean inputs for MMM and incrementality; ensure data fidelity and methodological consistency. Digest and socialize findings with clear implications for media mix, incrementality and market-level investment. Partner with brand, growth & media teams for holdout implementation and analysis for channel investment and large scale campaigns. Partner with finance on top of funnel business trends analysis on an ad-hoc basis (i.e. if we see conversion changes and need to dig into the source) Produce high-level readouts for big campaign moments: including pre-/post- and YoY comparisons. Combine business metrics (e.g., acquisition, revenue proxies, LTV indicators) with brand health metrics (e.g., QuestBrand/YouGov/Ipsos, platform brand-lift) to form a POV on whether objectives were met and what we learned. Support the VP, Global Marketing in \u201cstate of the business\u201d reviews across geographies. Surface country-level signals, opportunities, and risks; coordinate with Finance, Media, and Marketing to align on actions. Serve as the Global Marketing analytics point-of-contact with Match Group central analytics teams and external partners. Collaborate with Data Engineering/Analytics to QA pipelines and keep decision-grade data flowing. 7-10+ years in marketing/media analytics (consumer subscription or mobile/app experience a plus). Strong BI skills (Looker/Tableau/Data Studio); working fluency in Python/R for analysis and scenario modeling. Hands-on experience supporting MMM and incrementality/geo tests; proven ability to convert model outputs into budget decisions. Fluency with brand-lift methodologies and brand equity tracking (e.g., QuestBrand, YouGov, Ipsos) and how to integrate with performance KPIs. Executive presence: succinct storytelling, meeting facilitation, and stakeholder management across senior audiences. Data rigor: taxonomy design, QA habits, comfort with ambiguity, and bias to action. Familiarity with privacy-aware measurement and mobile attribution (e.g., AppsFlyer/Adjust) is a plus.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38762858", "isPrivate": false}, {"id": 38770281, "name": "Staff Machine Learning Engineer, Dating Outcomes", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1766379687, "t_create": 1762524302, "ats_job_id": "083c5419-56ce-4543-bcc3-5d7ae0f1a211", "display_job_id": "083c5419-56ce-4543-bcc3-5d7ae0f1a211", "type": "ATS", "id_locale": "7752792792892420355-en", "job_description": "Design and own foundational research and models that power our recommendations ecosystem. Identify the next step change in our technical capabilities, conduct state-of-the-art applied research, and move them into production using best practices in machine learning engineering. Design and implement solutions that prioritize availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters. Collaborate closely with Directors and VP+ to understand and shape Hinge's strategic direction, as well as work with other Machine Learning Engineers, Product Managers, Data Engineers, and Scientists to make that a reality. Coach, mentor, and educate Machine Learning Engineers on current and SOA research, technologies, and best practices of practicing machine learning at scale. Strong programming skills: Proficiency in languages like Python, Java, or C++ and a deep understanding of low-level deep learning computation fundamentals. System design & architecture: Proven track record of research, training, and deployment of DNNs at scale. Deep understanding of distributed computing for learning, data processing, and inference. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, Databricks, KubeFlow, or W&B is a plus. ML knowledge: Deep understanding of various DNN architectures, track record of building, debugging, and fine-tuning models. DevOps skills: Track record of deploying, managing, and orchestrating offline and online deep learning models at scale. Data engineering knowledge: Skills in handling and managing large datasets, including data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds. Proven ability to influence company strategy and direction is a plus. Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes. 8+ years of experience, depending on education, as an MLE. 4+ years of experience working in a cloud environment such as GCP, AWS, Azure, and with dev-ops tooling such as Kubernetes. 4+ years of experience in designing and developing online and production grade ML systems. 3+ years of experience leading projects with at least 2 other team members through completion. A degree in computer science, engineering, or a related field.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38770281", "isPrivate": false}, {"id": 38964202, "name": "Senior Machine Learning Engineer, Dating Outcomes", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1766379687, "t_create": 1763661427, "ats_job_id": "523e9382-57ad-45bb-a06d-c71e57bd0240", "display_job_id": "523e9382-57ad-45bb-a06d-c71e57bd0240", "type": "ATS", "id_locale": "6816203959448473200-en", "job_description": "Own and contribute to foundational models that power our recommendations ecosystem. Contribute to the research and development of models powering Hinge and experiment with the latest innovations in the field of Machine Learning (e.g., LLM agents, MMoE models, VAEs, etc.) Design, advocate for, and implement solutions that ensure availability, scalability, operational excellence, and cost management, while delivering incremental impact to our daters. Collaborate closely with other Machine Learning engineers, Product Managers, Data Engineers, and Scientists to understand our users' needs and identify opportunities to make their experience better through machine learning. Mentor and educate Machine Learning Engineers on current and SOA research, technologies, and best practices of practicing machine learning at scale. Strong programming skills: Proficiency in languages like Python, Java, or C++ System design & architecture: Proven track record of training and deploying large scale ML models, especially DNNs. Good understanding of distributed computing for learning, data processing, and inference. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, Databricks, KubeFlow, or W&B is a plus. ML knowledge: Deep understanding of DNN architectures, track record of building, debugging, and fine-tuning models. Familiarity with PyTorch, TF, knowledge distillation, and recommender systems is a plus. DevOps skills: The ability to establish, manage, and use data and compute infrastructure such as Kubernetes and Terraform. Data engineering knowledge: Skills in handling and managing large datasets, including data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds. Strong written communication: The ability to communicate complex ideas and technical knowledge through documentation Software leadership skills: A track record of leading projects through completion with quantifiable and measurable outcomes. 4+ years of experience, depending on education, as a Machine Learning Engineer. 2+ years of experience working in a cloud environment, such as GCP, AWS, or Azure, and with DevOps tooling, including Kubernetes. 2+ years of experience designing and developing online and production grade machine learning systems. 1+ year of experience leading projects with at least 1 other team member through completion. A degree in computer science, engineering, or a related field.", "stars": 0.0, "medallionProgram": null, "location_flexibility": null, "work_location_option": "onsite", "canonicalPositionUrl": "https://join.matchgroupcareers.com/careers/job/38964202", "isPrivate": false}, {"id": 20079076, "name": "Machine Learning Engineer", "location": "New York, New York", "locations": ["New York, New York"], "hot": 0, "department": "Hinge", "business_unit": "Engineering", "t_update": 1766379687, "t_create": 1705101155, "ats_job_id": "3fc3a7d4-4a84-4eb9-80d6-ab3c549c6171", "display_job_id": "3fc3a7d4-4a84-4eb9-80d6-ab3c549c6171", "type": "ATS", "id_locale": "203998211731315363-en", "job_description": "Own and contribute to foundational models (e.g. CLIP embeddings) that powers our recommendations pipelines. Contribute to the research and development of recommender models as well experiment with the latest ML innovations (e.g. LLM agents and transcription models) Design, advocate, and implement for availability, scalability, operational excellence, and cost management while delivering impact to our daters incrementally. Collaborate closely with ML Engineers, Data Scientists, and Product Managers to understand their needs and identify opportunities to accelerate the AI/ML development and deployment process. Mentor and educate ML Engineers on current and up and coming research, technologies and best practices of doing ML at scale. Perform other job-related duties as assigned. Strong programming skills: Proficiency in languages like Python, Java or C++ System design & architecture: Proven track record of training and deploying large scale ML models specially DNNs. Good understanding of distributed computing for learning and inference. Cloud platform proficiency: The ability to utilize cloud environments such as GCP, AWS, or Azure. Familiarity with ML serving solutions like Ray, KubeFlow or W&B is a plus. ML knowledge: Deep understanding of DNN architectures, track record of building, debugging and fine tuning models. Familiarity with PyTorch, TF, knowledge distillation, recommender systems are a plus. Dev-ops skills: The ability to establish, manage, and use data and compute infrastructure such as Kubenetes and Terraform. Data engineering knowledge: Skills in handling and managing large datasets including, data cleaning, preprocessing, and storage. Deep understanding of batch and streaming pipelines as well as orchestrators like Argo and Airflow. Collaboration and communication skills: The ability to work effectively in a team and communicate complex ideas clearly with individuals from diverse technical and non-technical backgrounds.. 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