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Internship Data Optimization Jobs in New York (NOW HIRING)

Sosemo

SEO Associate

Manhattan, NY · On-site

Utilize Excel and other data visualization tools to isolate trends and develop insights * Self ... Minimum of one internship in a related industry * Passion for digital marketing and ...

Sosemo

SEO Associate

Manhattan, NY · On-site

Utilize Excel and other data visualization tools to isolate trends and develop insights * Self ... Minimum of one internship in a related industry * Passion for digital marketing and ...

Optimum

Intern - Data Engineer

Long Island City, NY

$35/hr

Introducing Optimum Media. Driven by the power of Optimum, Optimum Media is our innovative ... internships, preferred * Experience scripting and deploying ETL jobs, cron jobs and code changes ...

Posted today

SEO

Vice President, Partner Relationships

New York, NY · On-site

$168K - $197K/yr

Hybrid - 3 days/week in the SEO office at 55 Exchange Place, New York, NY 10005 ABOUT SEO Founded ... Data, Reporting & Communication (10%) * Review partnership performance data and team insights to ...

YAI

Community Health Nursing Internship

Tarrytown, NY · On-site

$16 - $20.75/hr

Derive community diagnoses from physiological, psychological, social, and cultural data gathered ... Demonstrate effective communication with individuals, and families to promote optimum well-being.

YAI

Community Health Nursing Internship-10001

New York, NY · On-site

$16.50 - $21.25/hr

Derive community diagnoses from physiological, psychological, social, and cultural data gathered ... Demonstrate effective communication with individuals, and families to promote optimum well-being.

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Internship Data Optimization information

What are the key skills and qualifications needed to thrive as an intern in data optimization, and why are they important?

To thrive as an Internship Data Optimization professional, you need a solid understanding of data analysis, statistics, and basic programming skills, often supported by coursework or a degree in a related field. Familiarity with tools such as Excel, SQL, Python, and data visualization platforms is typically required. Strong attention to detail, problem-solving abilities, and effective communication are key soft skills that distinguish top candidates. These skills are essential for accurately analyzing data sets, identifying optimization opportunities, and clearly presenting actionable insights to stakeholders.

What is the difference between Internship Data Optimization vs Data Analyst?

AspectInternship Data OptimizationData Analyst
Required CredentialsTypically pursuing or recent graduate, some technical skillsBachelor's or higher in related field, technical proficiency
Work EnvironmentInternship setting, entry-level tasks, mentorshipFull-time, project-based, collaborative teams
Employer & Industry UsageInternship programs in tech, finance, marketingAcross industries, including tech, finance, healthcare
Search & Comparison IntentEntry-level, internship opportunities, learning rolesData analysis roles, career advancement

Internship Data Optimization focuses on entry-level, temporary roles aimed at learning data enhancement techniques, while Data Analysts are full-time professionals responsible for analyzing and interpreting data to support business decisions. Both roles require technical skills, but the internship is more educational and less specialized.

What types of projects and tasks can I expect to work on during an internship in data optimization?

As a Data Optimization intern, you will likely support projects involving data cleaning, analysis, and process improvement. Typical daily tasks may include preparing datasets, running statistical analyses, developing or optimizing algorithms, and visualizing results to help teams make data-driven decisions. You may also collaborate with data scientists and engineers to identify inefficiencies in data pipelines and propose solutions. This role offers valuable exposure to real-world business challenges, and interns often gain hands-on experience with popular data tools and programming languages, laying a solid foundation for future roles in data analytics or engineering.

What is an internship in data optimization?

An Internship in Data Optimization is a temporary position for students or recent graduates to gain practical experience in improving the efficiency and effectiveness of data processes within an organization. Interns typically work with data analysts and engineers to clean, organize, and analyze data, as well as implement optimization techniques to enhance data quality and performance. This role offers hands-on exposure to tools and technologies related to data management and analytics, making it an excellent opportunity to build foundational skills for a career in data science or analytics.
What are the most commonly searched types of Data Optimization jobs in New York? The most popular types of Data Optimization jobs in New York are:
What are popular job titles related to Internship Data Optimization jobs in New York? For Internship Data Optimization jobs in New York, the most frequently searched job titles are:
What job categories do people searching Internship Data Optimization jobs in New York look for? The top searched job categories for Internship Data Optimization jobs in New York are:
Internship Data Optimization jobs near you
Infographic showing various Internship Data Optimization job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Scientist, Portfolio Optimization

Formation Bio

New York, NY

$154K - $202K/yr

Other

Re-posted 13 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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