Applied Machine Learning Scientist 2 Job at Washington Post, Washington DC

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  • Washington Post
  • Washington DC

Job Description

Job Description

The Washington Post Personalization team is looking for an applied machine learning scientist who is excited to create forward-thinking solutions for the next generation of journalism. Our team is at the heart of the Post's machine learning strategies to build intelligent and adaptable personalized news experiences and business solutions capable of powering the most high-scale websites in the world.

Motivation
  • You value world-class journalism and are eager to immerse yourself in features and projects that support that mission.
  • You are a technically savvy critical thinker who enjoys problem-solving.
  • You receive feedback enthusiastically and thrive in a collaborative environment.
  • You are eager to evolve and grow your skill-set by learning and sharing the latest machine learning technologies.

Responsibilities
  • Collaborate with cross-functional agile teams of data scientists, machine learning engineers, software engineers, and others in building machine learning infrastructure that best supports the ML needs.
  • Have a strong problem-solving ability and a knack for statistical analysis.
  • Apply machine learning technologies to build statistical models with large amounts of data.
  • Analyze large and complex data sets to derive valuable insights, inform feature and product development.
  • Deploy ML models under the constraints of scalability, correctness, and maintainability.
  • Monitor and ensure the quality of machine learning solutions by implementing process and control disciplines as well as tooling to govern.
  • Proven ability to communicate with business and know business needs, and align our data products with our business goals.

Qualifications:

Minimum Qualifications
  • Bachelor's degree in Computer Science, Mathematics, Statistics, or related field
  • 2 year+ machine learning and data science experience
  • 1 year+ professional experience with Python

Preferred Qualifications
  • 2 year+ experience with AWS
  • 2 year+ experience with clustering, classification, sentiment analysis, time series, and deep learning
  • Knowledge in LLMs
  • Knowledge in Recommendation Systems
  • Knowledge in Economics, Finance, or related field
  • Ph.D. degree in Computer Science, Mathematics, Statistics, or related field

Compensation and Benefits

Wherever you are in your life or career, The Washington Post offers comprehensive and inclusive benefits for every step of your journey:
  • Competitive medical, dental and vision coverage
  • Company-paid pension and 401(k) match
  • Three weeks of vacation and up to three weeks of paid sick leave
  • Nine paid holidays and two personal days
  • 20 weeks paid parental leave for any new parent
  • Robust mental health resources
  • Backup care and caregiver concierge services
  • Gender affirming services
  • Pet insurance
  • Free Post digital subscription
  • Leadership and career development programs

Benefits may vary based on the job, full-time or part-time schedule, location, and collectively bargained status.

The salary range for this position is:
108,700.00 - 181,100.00 USD Annual

The actual salary within this range will depend on individual skills, experience, and qualifications as they relate to specific job requirements. This position may be eligible for a bonus or incentive program, and a member of the Talent Acquisition team will discuss bonus payment terms and conditions during the interview process.

The Post strives to provide its readers with high-quality, trustworthy news and information while constantly innovating. That mission is best served by a diverse, multi-generational workforce with varied life experiences and perspectives. All cultures and backgrounds are welcomed.

The innovation doesn't end in the Newsroom - dozens of teams power The Washington Post . We are now hiring the next innovator - how will you Impact Tomorrow ?

#washpostlife

Job Tags

Holiday work, Full time, Part time, Immediate start,

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