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Opt Cpt Data Science Jobs in Indiana (NOW HIRING)

... CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1. Preferred Qualifications ... Understanding of scientific data types and experimental workflows in life sciences or pharma ...

Recent computer science/engineering/mathematics/statistics or science graduates looking to make ... Different visa candidates (like OPT/H4EAD/L2EAD) who want to get employed and settle down in the ...

Entry Level Data Engineer

Indianapolis, IN

$109.40K - $131.40K/yr

Recent graduates in Computer Science, Engineering, Mathematics, Statistics, or related STEM fields ... To opt out, reply directly and request removal. * No phone calls, third-party agencies, or C2C ...

Recent computer science/engineering/mathematics/statistics or science graduates looking to make ... OPT/H4EAD/L2EAD) who want to get employed and settle down in the USA. REQUIRED SKILLS for Java ...

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Opt Cpt Data Science information

What are the key skills and qualifications needed to thrive as an Opt CPT Data Scientist, and why are they important?

To thrive as an Opt CPT Data Scientist, you need a solid background in statistics, programming (often in Python or R), and data analysis, typically supported by a related degree such as computer science, statistics, or engineering. Familiarity with tools like SQL, machine learning frameworks (e.g., TensorFlow, Scikit-learn), and data visualization platforms such as Tableau is often required, along with relevant certifications. Strong problem-solving abilities, communication skills, and teamwork are crucial soft skills that help you interpret complex data and convey insights effectively. These competencies are essential for extracting actionable value from data, supporting informed decision-making, and driving organizational success.

How do data scientists typically collaborate with cross-functional teams in an organization?

Data scientists frequently work alongside product managers, engineers, and business analysts to translate business challenges into data-driven solutions. This often involves participating in meetings to understand project goals, sharing progress updates, and presenting findings in a clear, actionable manner to both technical and non-technical stakeholders. Effective communication and teamwork are essential, as data scientists must ensure their insights are understood and can be integrated into business strategies or product development. Collaboration tools and agile methodologies are commonly used to streamline this process.

What are Opt CPT Data Science jobs?

Opt CPT Data Science jobs are positions in the data science field that are suitable for international students in the United States on F-1 visas who are authorized to work under Optional Practical Training (OPT) or Curricular Practical Training (CPT). These roles typically involve tasks such as data analysis, machine learning, statistical modeling, and data visualization. Employers hiring for Opt CPT Data Science jobs often consider candidates who require visa sponsorship and are familiar with the OPT/CPT process. The positions can be found across various industries such as technology, finance, healthcare, and retail. These roles help international students gain valuable work experience related to their field of study.

What is the difference between Opt Cpt Data Science vs Data Analyst?

AspectOpt Cpt Data ScienceData Analyst
Required CredentialsBachelor's or higher in Data Science, Computer Science, or related fields; certifications like CAP, Microsoft Certified Data AnalystBachelor's in Statistics, Mathematics, or related fields; certifications like Microsoft Certified Data Analyst
Work EnvironmentTech companies, finance, healthcare; focus on predictive modeling and machine learningBusiness, marketing, finance; focus on data visualization and reporting
Industry UsageCommon in tech, finance, healthcare sectorsWidely used across industries including retail, finance, and marketing

Opt Cpt Data Science and Data Analyst roles share foundational skills in data handling and analysis. However, Data Scientists often focus on advanced modeling and machine learning, while Data Analysts emphasize data visualization and reporting. Both roles are vital in data-driven decision-making but differ in complexity and scope.

What are popular job titles related to Opt Cpt Data Science jobs in Indiana? For Opt Cpt Data Science jobs in Indiana, the most frequently searched job titles are:
What cities in Indiana are hiring for Opt Cpt Data Science jobs? Cities in Indiana with the most Opt Cpt Data Science job openings:
Data Architect, Data Foundry

Data Architect, Data Foundry

Eli Lilly

Indianapolis, IN

$61 - $78.50/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 27 days ago


Eli Lilly and Company rating

8.8

Company rating: 8.8 out of 10

Based on 62 frontline employees who took The Breakroom Quiz

11th of 71 rated pharmaceutical


Job description

Data Architect, Data Foundry

Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities.

Data Foundry is a multidisciplinary team within DTP that enables AI-native drug discovery through four integrated pillars: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation & Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI-driven capabilities—serving both human scientists and autonomous AI agents.

We are seeking Data Architects at multiple levels to design and build the data infrastructure that makes AI-native drug discovery possible. You will create the schemas, ontologies, data models, knowledge graphs, and platform architectures that transform raw scientific data into machine-actionable, FAIR-compliant, insight-ready assets—serving both discovery scientists and autonomous AI agents.

This role is the foundation of Architecture4Insight. Everything the software engineering team builds—pipelines, APIs, prototypes—depends on the data models and platform architecture this team designs. You will work with deep knowledge of scientific data (chemical, biological, HTE, automation-generated) to create custom-fit solutions, then partner with Tech@Lilly to scale and maintain them. The role spans three focus areas depending on expertise: data modeling & ontologies, data platform & lakehouse architecture, and knowledge graph & specialized data systems.

Data Modeling & Ontologies
  • Design and implement data models, schemas, and ontologies for chemical, biological, and automation-generated data that serve discovery workflows across the portfolio.
  • Define and maintain controlled vocabularies, metadata standards, and FAIR-compliant data frameworks in partnership with Preparedness4Insight.
  • Implement semantic data standards (RDF, OWL, SPARQL) and ontology engineering practices to create interoperable, machine-readable scientific data.
Data Platform & Lakehouse Architecture
  • Design and implement data lakehouse architecture using modern platforms (Databricks, Snowflake, or equivalent), including data storage patterns, partitioning strategies, and query optimization.
  • Build and optimize ETL/ELT pipelines using Spark, dbt, or similar tools to transform raw scientific data into analytical and ML-ready formats.
  • Implement real-time and streaming data integration (Kafka, Kinesis, event-driven patterns) connecting LIMS, instruments, and lab automation systems to the data infrastructure.
Knowledge Graph & Specialized Data Systems
  • Design and implement knowledge graphs (Neo4j, Amazon Neptune, TigerGraph) that capture molecular, target, pathway, and experimental relationships across the discovery landscape.
  • Architect specialized data solutions: array databases (TileDB) for genomics/imaging, document stores (MongoDB) for experimental records, and vector databases for embedding-based retrieval supporting ML and RAG workflows.
  • Build query and traversal patterns that enable scientists and AI agents to ask relational questions across the entire data landscape.
Cross-Functional Partnership
  • Partner with scientific software engineers to ensure data architectures are implementable, performant, and well-documented.
  • Collaborate with Methods4Insight to design data structures that support analytical model training, deployment, and evaluation.
  • Work with Tech@Lilly to define scaling strategies, ensure enterprise compliance, and transition data architectures to production-grade management.
  • Contribute to build-versus-buy-versus-adopt decisions by evaluating commercial and open-source data platforms against Data Foundry requirements.
Basic Requirements
  • B.S. or M.S. in Computer Science, Data Science, Bioinformatics, Computational Biology, Information Science, or related STEM field; Ph.D. valued for ontology and knowledge graph roles.
  • B.S. with 7+ years and M.S. with 5+ years of data architecture, data engineering, or scientific informatics' experience.
  • SQL skills and experience in multiple database paradigms (relational, graph, document, columnar, key-value).
  • Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.
Preferred Qualifications
  • Expertise in at least one of: data modeling/ontologies, data platform engineering (Databricks, Snowflake, Spark), or graph/specialized databases (Neo4j, Neptune, MongoDB).
  • Familiarity with cloud platforms (AWS, Azure, or GCP) and modern data integration patterns.
  • Understanding of scientific data types and experimental workflows in life sciences or pharma (chemical, biological, HTE data).
  • Strong communication skills with ability to translate data architecture concepts for both technical and scientific audiences.
  • Pharmaceutical or biotech research industry experience, particularly in discovery data management or research informatics.
  • Experience with semantic web technologies: RDF, OWL, SPARQL, Protégé, or equivalent ontology engineering tools.
  • Hands-on experience with graph databases (Neo4j, Neptune, TigerGraph) and knowledge graph design patterns for scientific data.
  • Data lakehouse architecture experience: Databricks (Delta Lake, Unity Catalog), Snowflake, or equivalent; ETL/ELT with Spark, dbt.
  • Experience with streaming/real-time data platforms (Kafka, Kinesis, Flink) and event-driven architectures.
  • Familiarity with LIMS, ELN systems (e.g., Benchling), and laboratory instrument data integration.
  • Experience with vector databases (Pinecone, Weaviate, pgvector) and embedding-based retrieval for ML/RAG applications.
  • Array database experience (TileDB, Zarr) for genomics, imaging, or high-dimensional scientific data.
  • Experience with bioinformatics data formats (FASTA, BAM/CRAM, VCF) and biological sequence databases; familiarity with NGS data pipelines and proteomics data management.
  • FAIR data principles implementation experience and Data Readiness Level frameworks.
  • Scientific data standards and controlled vocabularies in chemistry (InChI, SMILES) or biology (Gene Ontology, UniProt, pathway databases such as Reactome or KEGG).

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women's Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.

Actual compensation will depend on a candidate's education, experience, skills, and geographic location. The anticipated wage for this position is $132,000 - $193,600.

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and


What Eli Lilly and Company employees say

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Eli Lilly logo

About Eli Lilly

Sourced by ZipRecruiter

Eli Lilly, based in Indianapolis, IN, US, is one of the pioneers in the pharmaceutical industry with a rich history dating back to 1876. This global pharmaceutical company focuses on discovering, developing, manufacturing and selling pharmaceutical products in approximately 120 countries. The company's product categories include endocrinology, oncology, cardiovascular, neuroscience, and immunology. Having invested over $9 billion in research and development in the past decade, Eli Lilly is also committed to creating high-quality medicines that meet real needs. As a recipient of several awards and recognitions, Eli Lilly is known for its focus on life-saving research and drug development. Their mission is to make medicines that help people live longer, healthier, and more active lives.

Industry

Pharmaceutical product wholesalers

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

1876