Machine Learning Scientist, Algorithmic Recommendations (Email Targeting)

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview The New York Times is committed to producing the world's most reliable and highest quality journalism. Our ability to do so relies on a talented team of expert technologists who help NYT learn from a tremendous abundance of data unique to this company. The Algorithmic Recommendations and Audience Data Science team aims to help users discover relevant content across the Times' website, apps, and emails. To achieve this, the team applies algorithms that make use of information about our readers' behavior and our editorial judgment. We also build internal tools for the newsroom to better understand story performance and coverage trends. We are looking for a Machine Learning Scientist to join the team and apply machine learning methods to our targeted email strategy. You will report to the lead of the AlgoRecs team. Responsibilities: You will reframe business and newsroom goals as machine learning tasks that deliver accurate predictions, relevant insights, and optimization You will implement and deploy machine learning research with robustness and reproducibility, with consideration of risks and trade-offs You will learn new technologies and ML methods, and adapt them into our workflows You will deploy models behind production APIs or batch processes, collaborate with engineering teams, and integrate into processes throughout The Times You will communicate complex ideas in machine learning while collaborating with all kinds of colleagues in in engineering, analytics, product management, marketing, editorial, and executive leadership groups Demonstrate support and understanding of our value of journalistic independence and a strong commitment to our mission to seek the truth and help people understand the world. Basic Qualifications: PhD, MS + 2 years experience, or 3+ years experience in statistics, computational social science, applied mathematics, economics, or another quantitative/computational discipline 2+ years experience with open source machine learning or statistical analysis tools 2+ years coding experience in Python 2+ years experience in SQL and manipulating large structured or unstructured datasets for analysis Experience in A/B testing or experimentation Preferred Qualifications: 1+ years of experience applying machine learning to email campaigns (optimizing timing, content selection, or audience creation) 1+ years of experience with recommendation systems, using natural language processing and large language models 1+ years of experience translating ambiguous business questions into machine learning problems 1+ years of experience building data products, either internal or consumer-facing REQ-020137 The annual base pay range for this role is between: $121,000 — $131,000 USD For roles in the U.S., dependent on your role, you may be eligible for variable pay, such as an annual bonus and restricted stock. Benefits may include medical, dental and vision benefits, Flexible Spending Accounts (F.S.A.s), a company-matching 401(k) plan, paid vacation, paid sick days, paid parental leave, tuition reimbursement and professional development programs. For roles outside of the U.S., information on benefits will be provided during the interview process. We’re excited to learn more about you and your experience. To keep our hiring process as fair and authentic as possible, we ask that you submit your own work and not use GenAI tools to generate substantive content during the application and interview process. If you’re an Engineering candidate, we’ll let you know what specific GenAI tools you are permitted to use for your technical assessment. The New York Times Company is committed to being the world’s best source of independent, reliable and quality journalism. To do so, we embrace a diverse workforce that has a broad range of backgrounds and experiences across our ranks, at all levels of the organization. We encourage people from all backgrounds to apply. We are an Equal Opportunity Employer and do not discriminate on the basis of an individual's sex, age, race, color, creed, national origin, alienage, religion, marital status, pregnancy, sexual orientation or affectional preference, gender identity and expression, disability, genetic trait or predisposition, carrier status, citizenship, veteran or military status and other personal characteristics protected by law. All applications will receive consideration for employment without regard to legally protected characteristics. The U.S. Equal Employment Opportunity Commission (EEOC)’s Know Your Rights Poster is available here . The New York Times Company will provide reasonable accommodations as required by applicable federal, state, and/or local laws. Individuals seeking an accommodation for the application or interview process should email [email protected]. Emails sent for unrelated issues, such as following up on an application, will not receive a response. The Company encourages those with criminal histories to apply, and will consider their applications in a manner consistent with applicable "Fair Chance" laws, including but not limited to the NYC Fair Chance Act, the Los Angeles Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act. For information about The New York Times' privacy practices for job applicants click here . Please beware of fraudulent job postings. Scammers may post fraudulent job opportunities, and they may even make fraudulent employment offers. This is done by bad actors to collect personal information and money from victims. All legitimate job opportunities from The New York Times will be accessible through The New York Times careers site . The New York Times will not ask job applicants for financial information or for payment, and will not refer you to a third party to do so. You should never send money to anyone who suggests they can provide employment with The New York Times. If you see a fake or fraudulent job posting, or if you suspect you have received a fraudulent offer, you can report it to The New York Times at [email protected]. You can also file a report with the Federal Trade Commission or your state attorney general .

{
  "content_hash": "811fb72c757f3dec060b1ce438dbb74ceb11791bd08941d201b7b71034739980",
  "source_hash": "6703165f1065cd9f7500412a4e16ada987ffafe7ba062d806fbeefcd932c0e1f",
  "last_changed_at": "2026-06-06T07:31:57.011Z",
  "active_status": "active"
}

{
  "language": "en",
  "location": {
    "raw": "New York, NY",
    "city": "New York",
    "region": "NY",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 131000,
  "salary_min": 121000,
  "inferred_at": "2026-06-06T19:36:22.108Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "New York, NY",
      "city": "New York",
      "region": "NY",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
    },
    "countries": [
      "United States"
    ]
  },
  "remote_policy": null,
  "salary_period": "year",
  "workplace_type": null,
  "salary_currency": "USD"
}

{}

{
  "title": "Machine Learning Scientist, Algorithmic Recommendations (Email Targeting)",
  "offices": [
    {
      "id": 4011782005,
      "name": "New York, NY",
      "location": null,
      "child_ids": [],
      "parent_id": 4011645005
    }
  ],
  "language": "en",
  "location": {
    "name": "New York, NY"
  },
  "metadata": [],
  "updated_at": "2026-05-28T12:20:08-04:00",
  "departments": [
    {
      "id": 4030390005,
      "name": "Data Science",
      "child_ids": [],
      "parent_id": 4030230005
    }
  ],
  "company_name": "The New York Times",
  "requisition_id": 4437829005,
  "first_published": "2026-05-27T16:37:51-04:00",
  "application_deadline": null
}