
Data Scientist
NEW YORK, NYJob$81–158K/yrSeen 1w agoSeen in employer's feed 1 day ago
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At a glance
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Job overview
Mphasis seeks a Data Science Lead to drive complex machine learning, NLP, and LLM initiatives. The role owns solution architecture, quality standards, and technical direction while mentoring teams and advising stakeholders. The lead also guides ML programs, establishes evaluation and governance practices, and advises business and leadership on strategy and feasibility.
Skills & qualifications
Skills
Qualifications
Full job description
M-114579-11-1 Data Science Lead Experience Level: 812 YearsRole SummaryTechnical leader responsible for driving complex ML, NLP, and LLM initiatives. Owns solution architecture, quality standards, and technical direction while mentoring teams and advising stakeholders.Key Responsibilities * Lead largescale data science and ML programs. * Define NLP and LLM solution approach and architecture. * Set standards for model evaluation, monitoring, and governance. * Guide teams on best practices across ML lifecycle. * Advise business and leadership on ML strategy and feasibility. * Stay current on emerging ML and LLM technologies.Mandatory / Key Skills (with expected experience) * Advanced Python and ML systems design: 812 years * Endtoend ML delivery in production environments: 812 years * NLP for enterprisescale use cases: 68 years * LLM ecosystem (design choices, evaluation, tradeoffs): 57 years * Model evaluation, monitoring, and risk management: 68 years * Cloudnative ML architectures: 57 years * Technical leadership and stakeholder communication: 68 yearsEducationBachelors / Masters / PhD in Computer Science, Data Science, Engineering, or related field.Process & Ways of Working * Strong understanding of SDLC, Agile, and Scrum methodologies. * Ability to gather requirements, create technical designs, and write clear documentation. * Participate in code reviews and ensure best engineering practices.Behavioral & Soft Skills * Excellent problem-solving and analytical thinking. * Strong communication and collaboration skills across cross-functional teams. * Self-driven, adaptable, and eager to learn new technologies.Other detailsSalary range $80500 to $157500Equal opportunity Employer:Mphasis is an equal opportunity/affirmative action employer. We provide equal employment opportunities to applicants and existing associates and evaluate qualified candidates without regard to race, gender, national origin, ancestry, age, color, religious creed, marital status, genetic information, sexual orientation, gender identity, gender expression, sex (including pregnancy, breast feeding and related medical conditions), mental or physical disability, medical conditions military and veteran status or any other status or condition protected by applicable federal, state, or local laws, governmental regulations and executive orders.VEVRAA Federal Contractor.We request Priority Protected Veteran & Disabled Referrals for all of our locations within the state.
How this job compares
Set against the 5,105 open Data Scientist jobs on Olive Jobs, counted October 29, 2026.
- Pay
- This posting$81–158K/yr
- New York median$149–211K/yr366 salary ranges
- US median$135–216K/yr4,092 salary ranges
This range's midpoint, $119K, is 36% below the New York median midpoint ($185K) — in the lowest quarter of Data Scientist salary ranges in New York.
- Openings
- Olive Jobs lists 468 open Data Scientist jobs in New York and 5,105 across the US. 6% of them nationwide are listed as remote or flexible.
- Hiring the most in New York
- Capital One45 open
- PwC25 open
- Deloitte24 open
- Experience
- This posting asks for at least 8 years of experience — more than three in four Data Scientist postings that state a minimum ask for (median 5 years, across 4,402 postings).
- Education
- 2,829 of the 5,105 open Data Scientist jobs (55%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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