Summer Internship – IT & Data Analytics Intern (AI/ML Focus) 

Location:                      Irving, TX (On-Site) 
Department:                 Meriton IT & Data Analytics 
Internship Type:          Summer Internship (Full‑Time) 
Reports To:                  Hiring Manager – Meriton Technology & Analytics 

 If you’re looking to make an impact, we’re glad you’re here. At Meriton, you’ll join a team that believes in big ideas, doing great work, and building careers that matter—every step of the way. 

About the Role 

Meriton is seeking a highly motivated IT & Data Analytics Intern with a strong interest in Artificial Intelligence, Machine Learning, and Data Science. This role is ideal for students who enjoy problem‑solving, exploring emerging technologies, and applying analytics to drive insights and operational excellence. 

You’ll work closely with the Meriton technology team to support internal analytics, automation projects, and AI‑driven initiatives that enhance business decision‑making and improve efficiency. 

Key Responsibilities 

AI & Data Analytics 

• Assist in building and evaluating machine learning models, including data preprocessing, feature engineering, and model validation. 

• Use tools such as Cursor, Claude Code, AI Foundry, and similar AI development platforms to prototype automation and analytics solutions. 

• Conduct exploratory data analysis (EDA) on structured and unstructured datasets. 

• Support the creation of dashboards, reports, and visualizations for business stakeholders. 

• Research and recommend AI use cases that align with team strategy and business needs. 

IT & Technical Support 

• Collaborate with IT partners to streamline workflows through scripts, automation, and analytics. 

• Troubleshoot data, system, or integration issues as needed. 

• Document technical processes, workflows, and best practices. 

AI Product & Tooling Initiatives 

• Experiment with generative AI tools to assist with:  

• Query generation 

• Code generation & refactoring 

• Data pipeline development 

• Business insights summarization 

• Workflow automation 

• Partner with team members to test, evaluate, and implement AI‑powered solutions. 

Required Qualifications 

• Currently pursuing a degree in Computer Science, Data Science, Information Systems, Statistics, Engineering, or related fields. 

• Foundational coursework or hands‑on experience in:  

• Artificial Intelligence / Machine Learning 

• Data Science methodologies 

• Python, R, SQL, or similar languages 

• Comfortable working with modern AI coding tools such as:  

• Cursor (AI coding environment) 

• Claude Code / Claude AI 

• AI Foundry or other LLM ops platforms 

• Strong analytical thinking, problem‑solving abilities, and attention to detail. 

• Eagerness to learn, experiment, and adopt emerging technologies. 

Preferred Qualifications 

• Experience with:  

• Jupyter Notebooks 

• Pandas, NumPy, Scikit‑Learn, PyTorch or TensorFlow 

• Git / version control 

• Power BI or Tableau 

• Familiarity with API calls, cloud platforms, or DevOps automation. 

• Prior hands‑on project work involving AI agents, ML modeling, or generative AI use cases. 

Meriton is an equal opportunity employer

Hi, we're Oscar. We're hiring a to join our Clinical Data Analytics team.

Oscar is the first health insurance company built around a full stack technology platform and a relentless focus on serving our members. We started Oscar in 2012 to create the kind of health insurance company we would want for ourselves—one that behaves like a doctor in the family.

About the role:

You will partner closely across the organization to identify and manage inefficiencies proactively in the business. You will support business units in scoping, analyzing and monitoring performance of key financial and utilization metrics in service of company goals. You will independently drives the scoping & execution of analytical requests, including working with stakeholders to define key questions, scope methodologies and results. You will be called upon to speak to prepared analysis both internally and externally.

You will report into the Senior Manager, Clinical Analytics.

Work Location: This is a remote position, open to candidates who reside in: Dallas, Texas. You will be fully remote; however, our approach to work may adapt over time. Future models could potentially involve a hybrid presence at the hub office associated with your metro area. #LI-Remote

Pay Transparency: The base pay for this role is: $91,659 - $120,303 per year. You are also eligible for employee benefits, participation in Oscar's unlimited vacation program, and annual performance bonuses.

Responsibilities:

• Responsible for owning insights generation and follow-up for a major business unit, serving as the first point of contract for Sr. Managers and Associate Directors
• Analyze data to support business teams in making better informed, data-driven decisions
• Use data to tell a story that non-technical colleagues will be able to understand, including packaging and presenting findings in a clear, concise and compelling manner
• Recognize the need to enhance essential operational and analytical dashboards, and define the requirements to enhance them as our user's needs evolve
• Identify opportunities to create models and tools that produce relevant insights to identify healthcare inefficiencies and generate insights to remove inefficiencies
• Collaborate across the organization, including owning stakeholder relationships with managers & senior managers , to identify actions to achieve improvements and monitor initiative impact
• Support other strategic projects as assigned to meet business needs
• Compliance with all applicable laws and regulations
• Other duties as assigned

Requirements:

• 3+ years of technical work experience using analytical tools and writing analytical reports
• 3+ years demonstrated ability to work with large datasets and distill analyses into relevant insights with a structured and systematic thought process
• Strong communication skills, verbal and written, around business reporting impact and requirements, as demonstrated by 5+ examples / projects of presenting analysis to Leadership (Director+)
• 3+ years experience in SQL, with the ability to filter, aggregate, and build CTEs, or proficiency in R or Python, including experience with Pandas, for loops, and statistical tests
• 3+ years experience developing dashboards and working with Looker, or other business intelligence/data visualization tools
• 3+ years experience, including proficiency in Google Sheets or Excel skills, with ability to use VLookup, nested if statements and connected Sheets
• 1+ years experience in healthcare, consulting, finance or the insurance industry

Bonus points:

• 2+ years experience in preparing healthcare analytics and reporting
• 2+ years experience managing value-based contracts at a payer or a provider organization (ACO, CIN, MSO etc.)
• Exposure to healthcare contract negotiations, risk adjustment, ACA marketplace, quality of care, and/or population health experience

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

Role Description

• As a Senior Value Engineer specializing in the Energy Sector, you are pushing the envelope in solving business-critical problems for our strategic customers across utilities, oil & gas, and renewable energy. You will be working with our most strategic energy clients, understanding their unique objectives—from grid modernization and asset lifecycle management to navigating the energy transition—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.
  
  With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape.

Key Responsibilities:

• AI Discovery & Solutioning: Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.

• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).

• Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector (Utilities, Oil & Gas, and/or Renewables). This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization.

• Deep understanding of business processes native to the Energy sector (such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., automated processing of engineering documents, regulatory filings, or intelligent diagnostic chatbots).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data.

• Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly regulated industries.

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with IT/OT convergence and industrial IoT data structures.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Business Intelligence & Data Analyst

Location: Hybrid
Type: Full-Time
Reports to: Director of Business Intelligence

We're looking for an analytically strong, hands-on BI & Data Analyst with 3-5 years of experience turning data into decisions. In this role, you'll own our Power BI environment, work directly in Microsoft Fabric, and partner across the business to deliver reporting and insights that drive better decisions.

About MyFundedFutures

MyFundedFutures (MFF) is a fast-growing futures evaluation and trading firm built for the next generation of global traders. We sit at the intersection of capital markets, technology, and risk, giving traders the tools, capital, and infrastructure to succeed.

Our data platform is already built on Microsoft Fabric using a Medallion architecture (Bronze, Silver, Gold), with clean, structured data flowing across trading platforms, CRM, risk engines, payments, support, and marketing data. The foundation is in place. Now we need someone to expand our Power BI ecosystem across the business and help strengthen a culture where decisions are backed by data.

What You'll Be Doing

Data & Reporting

• Own our Power BI environment end to end, including semantic models, DAX, and dashboards for executive leadership, risk, finance, operations, marketing, and support.
• Maintain and improve data pipelines in Microsoft Fabric, including Data Pipelines, Dataflows, and Notebooks, to keep data flowing reliably across the business.
• Build scalable data models using star schema and fact/dimension design principles.
• Deliver automated daily, weekly, and monthly reporting that gives teams timely, reliable access to key metrics.

Analysis & Insights

• Analyze trader behavior, including success rates, churn, risk signals, and anomalies.
• Support pricing, product, and growth decisions through scenario modeling, sensitivity analysis, and financial performance reviews.
• Identify early warning signals in risk and operational data before they become larger issues.

Cross-Functional Partnership

• Partner closely with the COO, Risk, Finance, Marketing, Product, and Support teams to translate business questions into analytical frameworks and actionable insights.
• Act as a trusted internal partner who helps teams understand what is happening in their area of the business and why.

What We're Looking For

Required

• 3-5 years of experience in business intelligence, data analytics, or a related field.
• Strong SQL skills, including complex queries, CTEs, window functions, and performance tuning.
• Hands-on Power BI experience, including semantic models, DAX, and business-critical reporting.
• Python and/or PySpark experience for data work, including pandas, scripting, API calls, and automation.
• Strong data modeling fundamentals, including schema design, grain definition, and scalable reporting structures.
• Experience with Microsoft Fabric or a comparable platform such as Azure Synapse, Data Factory, or Databricks.
• Experience integrating data from APIs, webhooks, or third-party SaaS platforms.
  
  

Nice to Have

• Experience in capital markets, futures trading, prop firms, or brokerage operations.
• Familiarity with drawdowns, leverage, volatility, and liquidation concepts.
• Experience working with financial time-series data.
• Interest in machine learning use cases such as churn prediction, anomaly detection, and forecasting, with openness to tools such as AutoML and MLflow as that capability evolves.

How You Work

• You translate complex data into clear, practical narratives for non-technical stakeholders.
• You work autonomously and are comfortable taking initiative in a fast-moving environment.
• You bring a strong sense of ownership and follow through on problems from identification to resolution.
• You are comfortable operating in ambiguity and can create structure when priorities are evolving.
• You think critically and creatively, challenge assumptions, and look for better ways to solve problems.

Why MFF

• Help shape how a high-growth trading firm makes decisions.
• Work alongside experienced operators from capital markets, fintech, and trading technology.
• Flexible work environment focused on outcomes and impact.
• Competitive compensation and meaningful room to grow as the company scales.

ICON is seeking a Senior Software/Data Engineer I to join our Data Intelligence & Systems Architecture (DISA) team. This engineer will play a foundational role in shaping, developing, and scaling ICON’s enterprise data platform within Palantir Foundry, owning the ingestion, modeling, and activation of data that powers reporting, decision-making, and intelligent automation across the company.

You will not just build pipelines. Instead, you will be architecting the Digital Twin of an industrial robotics and construction company. You will work closely with teams across Supply Chain & Manufacturing, Logistics, Engineering Support Services, Software, Field Operations and Technology R&D to centralize high-value data sources, model them into scalable assets, and enable business-critical use cases. Use cases will range from real-time reporting and analytics to AI/ML-driven operational workflows and decision-making. 

This is a highly cross-functional and technical role, ideal for someone with strong data engineering skills, deep business curiosity, and a bias toward action. This role is based at ICON’s headquarters in Austin, TX and reports to the Senior Director of Operations.

Responsibilities

• Data Pipeline Development: Design, build, and maintain scalable ETL/ELT pipelines in Palantir Foundry (and supplemental tools) to integrate data from enterprise systems (NetSuite, Workday, etc.) and external sources. Ensure pipelines are efficient and fault-tolerant, handling large data volumes from manufacturing and field operations (e.g. IoT sensor feeds).
• Data Modeling & Ontology: Develop and refine data models that organize enterprise data into meaningful structures. Leverage Foundry’s ontology features to define business objects (e.g. Customers, Work Orders, Inventory Items) and ensure data is linked in a way that reflects real-world relationships. Continuously improve these models for new business requirements – for instance, adding new attributes or new object types as we launch new programs.
• Data Quality & Governance: Implement data validation and quality checks in pipelines to ensure data accuracy and consistency. Monitor pipeline runs and set up alerts for anomalies or failures. Work with the team to enforce data governance policies (who owns which data, access controls, compliance needs) within Foundry and downstream systems.
• Cross-Functional Support: Collaborate with Data Analysts and business stakeholders to understand their data needs and optimize data outputs for analysis. For example, if Finance needs a specific revenue recognition report, ensure the pipeline provides the needed granularity. Provide ad-hoc data expertise to troubleshooting data issues or generating one-time analyses.
• Performance Optimization: Profile and tune data pipelines for performance. Optimize query logic, pipeline configuration, and resource usage so that data refreshes and analytics can occur in a timely manner (especially as data volumes grow with company expansion). Manage scheduling and orchestration of jobs to meet SLAs for data availability (e.g. daily financial report refresh by 8 AM).
• Integration with Systems: Work closely with Systems Architects to coordinate how data flows tie into system integrations. For example, if a new API integration is bringing in a type of data, design the pipeline to ingest that data and join it with relevant datasets for analytics. Provide input on what data transformations could happen in-flight vs. in Foundry to maximize efficiency.
• Tooling & Innovation: Contribute to developing internal tools or scripts to improve our data engineering workflow. This could include scripts for automating data deployments, custom plugins in Foundry, or using open-source frameworks (where applicable) to complement Foundry’s capabilities. Also evaluate new features in Foundry and emerging data technologies to keep our stack modern.
  
  
• Mentorship & Best Practices: As a senior member, guide junior data engineers in writing clean, maintainable pipeline code. Establish best practices for code versioning, documentation of data transformations, and general data engineering standards within the team.

Minimum Qualifications

• 7+ years of experience in data engineering or ETL development, handling large-scale datasets and complex pipelines. Strong foundation in data integration concepts and database design.
• Advanced Python skills for data processing (Pandas, etc.) and scripting, as well as solid SQL skills for querying and transforming data. Experience with PySpark or similar distributed data frameworks is a plus (Foundry uses Spark under the hood for big data).
• Experience building pipelines with enterprise data from systems like ERP, CRM, HRIS, or IoT sources. Familiar with different data formats (JSON, CSV, XML) and methods of extracting data (REST APIs, webhooks, database connectors).
• Hands-on experience with a modern data platform or pipeline orchestration tool. Experience with Palantir Foundry is a strong plus, but experience with alternatives (e.g. AWS Glue, Azure Data Factory, Databricks, Airflow, dbt, etc.) is acceptable if coupled with ability to learn Foundry quickly.
• Solid understanding of data modeling principles (relational schemas, star/snowflake schemas for analytics, normalization vs. denormalization tradeoffs). Ability to design schemas and data transformations that meet analytics requirements efficiently.
• Problem-solving and debugging skills: Able to investigate data discrepancies across systems, troubleshoot pipeline failures, and optimize slow queries.
• Attention to detail and commitment to data quality – recognizes the downstream impact of data issues and proactively puts checks in place.
• Good communication skills and ability to work with end users (analysts, managers) to clarify requirements. Comfortable explaining technical concepts to non-technical stakeholders when necessary.
• Bachelor’s degree in Computer Science, Data Engineering, or related field (or equivalent practical experience).

Preferred Skills & Experience

• Prior experience in a manufacturing or logistics environment where you dealt with IoT data, sensor streams, or other high-volume operational data. Understanding the nuances of such data (e.g. time-series data management) can be useful.
• Familiarity with cloud data architectures (AWS or Azure data services) as Foundry operates in cloud environments. Knowledge of storage services (S3, ADLS), data warehousing (Snowflake, Redshift), and how they integrate with pipeline tools.
• Experience with business intelligence tools or practices – able to appreciate how data will be used in dashboards or analytics so you can better tailor data outputs (experience with tools like Tableau, Power BI, or Foundry’s Contour/Quiver dashboards).
• Knowledge of DevOps and CI/CD for data pipelines – using version control (Git), and deploying code in a controlled, automated way.
• Master’s degree in Data Engineering or related field, or relevant certifications (e.g. Google Professional Data Engineer, AWS Data Analytics Specialty) indicating a commitment to ongoing learning in the field.