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Trainee Biotech Data Science Jobs in New York (NOW HIRING)

Amgen

Sr. Data Scientist - Process Modeling

Newark, NJ · On-site

... data science. * Chemical Engineering modeling, drug-substance, tech-transfer experience * 3+ years of work experience in biotechnology role (e.g. process engineer, scientist, data scientist)

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Arlyn AI

Principal / Senior Data Scientist

New York, NY · Remote

$175K - $255K/yr

You'll work at the intersection of AI, data science, and healthcare, helping biotech and pharma companies navigate patient access barriers and optimize commercial decisions. What You'll Do * Own the ...

Arlyn AI

Principal / Senior Data Scientist

Manhattan, NY · On-site

$175 - $255/hr

You'll work at the intersection of AI, data science, and healthcare, helping biotech and pharma companies navigate patient access barriers and optimize commercial decisions. What You'll Do * Own the ...

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Trainee Biotech Data Science information

What is the difference between Trainee Biotech Data Science vs Junior Biotech Data Analyst?

AspectTrainee Biotech Data ScienceJunior Biotech Data Analyst
Required CredentialsBachelor's in biotech, data science, or related fieldBachelor's in biotech, life sciences, or related field
Work EnvironmentResearch labs, biotech companies, data-focused projectsBiotech firms, research institutions, data reporting
Industry UsageData science, machine learning, bioinformaticsData analysis, reporting, data management
Common Search/ComparisonYesYes

The Trainee Biotech Data Science role focuses on applying data science and bioinformatics techniques within biotech settings, often involving machine learning and programming. In contrast, a Junior Biotech Data Analyst primarily handles data reporting and basic analysis. Both roles require a background in biotech or related fields, but the data science trainee emphasizes advanced data modeling, while the analyst concentrates on data interpretation and reporting.

What are the most commonly searched types of Biotech Data Science jobs in New York?

The most popular types of Biotech Data Science jobs in New York are:

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For Trainee Biotech Data Science jobs in New York, the most frequently searched job titles are:

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The top searched job categories for Trainee Biotech Data Science jobs in New York are:

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Cities in New York with the most Trainee Biotech Data Science job openings:

Trainee Biotech Data Science jobs near you
Infographic showing various Trainee Biotech Data Science job openings in New York as of June 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Scientist, Portfolio Optimization

New York, NY • On-site

Formation Bio
Biotechnology Research and Development • 51 - 200 employees
Learn more about Formation Bioexternal

$154K - $202K/yr

Full-time

Re-posted 6 days ago

Job description

About the Position 

As a Data Scientist on the platform prediction team, you'll translate our probability of success predictions into measurable portfolio-level outcomes. You'll architect core systems - order management, execution simulation, portfolio construction, risk monitoring, and performance attribution - that let us rigorously evaluate signals from our AI-driven predictions in public and private equities and our internal portfolio.

This role sits at the intersection of quantitative finance, healthcare data, and AI-driven drug development. If you're excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.No other company - hedge fund or pharma - has a technical data science position translating drug development experience into durable AI-native portfolio strategies. The skills you develop here - portfolio construction over assets with radically asymmetric risk profiles, clinical trial analytics, AI/ML in production, and risk management across multi-year horizons - can directly impact the delivery of new and effective therapeutics to patients by best aligning impactful medicines with economic incentives.

Responsibilities

  • Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
  • Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
  • Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
  • Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
  • Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
  • Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization

About You 

Required Qualifications

  • PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
  • 1-3 years in a quantitative research, data science, or analytics role in life sciences or life science adjacent field (healthcare, academic research, or consulting all count; substantive internships qualify)
  • Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
  • Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
  • Demonstrated ability to work with messy, real-world datasets - comfortable with data wrangling, deduplication, and quality assessment
  • Clear communicator who can present quantitative results to both technical peers and business stakeholders

Preferred Qualifications

  • Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
  • Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
  • Familiarity with alternative data in a research or investment context
  • Experience with probability-of-success modeling, drug development decision analysis, or health economics
  • Comfort with LLMs or AI/ML pipelines in a production or research setting
  • Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Healthcare OR finance domain knowledge is valued; both are not required.

Total Compensation Range: $154,500 - $202,000

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