> Markdown version of [/jobs/ext/3569709-senior-data-scientist](https://www.wearedevelopers.com/jobs/ext/3569709-senior-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior Data Scientist

- **Company:** DMI, LLC
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Computer Programming, Data Governance, Database Queries, Machine Learning, Strategies of Testing, Real Time Systems, Pyspark, Information Technology, Machine Learning Operations, Data Pipelines
- **Published:** October 3, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pouasukhdg

## About the Role

* Proficiency in Python/R
 * Pyspark and cloud tech exposure is a plus
 * Expertise in SQL querying
 * Product and model deployment on cloud platforms like GCP/AWS, * Qualifications preferred: PhD/Masters/Bachelors in Statistics, Engineering, Economics, Machine learning, Computer science, IT etc.

Work Experience

 * Proven experience of 4+ year of relevant experience
 * Other skills - Data Interpretation, Visualization, Programming
 * Knowledge of underlying mathematical foundations of statistics, ML and analytics
 * Experience in EDA, model development and validation
 * Experience in building and evaluating algorithms and optimizing the ML models in production
 * Experience in productionizing algorithms for real - time systems
 * Experience in influencing product and sourcing strategies with data centric presentations
 * Experiencing with statistics for statistical inferences, testing strategies, evaluating regression problems

## Description

1. Visualizing the scope of the project end to end
 * Identify the expected outcome
 * Figure out the data present and required for successful completion of the project
 * Defining the scope and effort needed for project execution
 * Devising monitoring frameworks

 2. Stakeholder management
 * You should be able to communicate with business stakeholders proactively to find out their pain points and propose a data backed solution to them
 * Should be able to formulate the complete steps to execution of the project with clarity on timelines
 * Should be good with data storytelling to ensure analytical models are easy to consume for different business functions

 3. Data standardization and integrity efforts
 * Ensuring we keep sanitizing our data sources and keep raising flags to functions who own these data sources for data issues
 * Ensure checks and reporting engines are in place to pick up anomalies in data pipeline

 4. Project management
 * Ensure timely closure of projects on or before committed timelines
 * Step by step monitoring of Projects from whiteboarding to deployment
 * Ensure model monitoring and communication around unusual spikes (if any)

 5. Mentoring
 * Mentoring junior resources on their projects
 * You must bring your industry experience into the project to ensure junior resources are able to correlate their work with business impact