Sr. Data ScientistOmm IT Solutions • Cary, NC, us

Sr. Data Scientist

Omm IT Solutions • Cary, NC, us

[job_card.variable_days_ago]

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[job_card.full_time]

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Job Description

PLEASE NOTE :

It is a 100% Onsite position at Cary, NC

JOB DESCRIPTION :

We are seeking an experienced and highly motivated Senior Data Scientist / Senior Data Science Engineer. This individual will play a key role in designing, implementing, and delivering cutting‑edge data science solutions that address complex business challenges.

The ideal candidate brings deep technical expertise, strong analytical capabilities, and hands‑on experience working in cloud-based environments—preferably Google Cloud Platform (GCP).

This role requires strong end‑to‑end ownership of the data science lifecycle, from data ingestion and modeling to deployment and evaluation, along with the ability to influence strategy and drive innovation.

SKILL SET :

Python, GCP (BigQuery, Dataflow, Dataproc, AI Platform)

KEY RESPONSIBILITIES :

Lead and deliver data science projects aligned with business strategy and performance targets.

Implement end‑to‑end data science workflows including data collection, preprocessing, feature engineering, model development, deployment, monitoring, and optimization.

Ensure model quality, reproducibility, and robustness.

Apply advanced statistical modeling, machine learning, and data mining techniques to solve complex business problems.

Build and deploy predictive models, optimization engines, recommender systems, NLP models, and other AI / ML solutions.

Work with big data technologies and cloud-native tools—preferably GCP, including BigQuery, Dataflow, Dataproc, AI Platform, Vertex AI, Airflow, or equivalent.

Write high-quality, production-ready code primarily in Python, following MLOps and software engineering best practices.

Present model insights, performance metrics, and recommendations to senior managers and stakeholders.

Contribute to roadmap planning, project scoping, and solution architecture discussions.

Stay current with the latest trends in machine learning, AI frameworks, and cloud technologies.

Evaluate emerging methodologies, tools, and algorithms to enhance data science capabilities.

Propose innovative solutions that improve model performance, scalability, and business impact.

Requirements

REQUIRED QUALIFICATIONS :

Master’s degree or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field.

10+ years of experience in data science, machine learning, applied analytics, or related disciplines.

Experience in financial services, banking, insurance, or fintech.

Proven experience developing, deploying, and operationalizing AI / ML solutions with measurable business impact.

Strong programming skills in Python, including experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).

Expertise working with cloud platforms, with strong preference for Google Cloud Platform (GCP) - BigQuery, Dataflow, Dataproc, AI Platform, Vertex AI, etc.

PREFERED QUALIFICATIONS :

Familiarity with data visualization tools such as Tableau or Looker.

Experience with MLOps practices and tools, including CI / CD pipelines for ML, model monitoring, and automated retraining.

Experience with feature stores, model registries, and large‑scale ML deployment.

Requirements

Master’s degree or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related field. 10+ years of experience in data science, machine learning, applied analytics, or related disciplines. Experience in financial services, banking, insurance, or fintech. Proven experience developing, deploying, and operationalizing AI / ML solutions with measurable business impact. Strong programming skills in Python, including experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Expertise working with cloud platforms, with strong preference for Google Cloud Platform (GCP) - BigQuery, Dataflow, Dataproc, AI Platform, Vertex AI, etc. Familiarity with data visualization tools such as Tableau or Looker. Experience with MLOps practices and tools, including CI / CD pipelines for ML, model monitoring, and automated retraining. Experience with feature stores, model registries, and large‑scale ML deployment

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