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Data Scientist

Net2Source (N2S) • Contract • Bellevue, WA, US • $60 - $70 / hour • 1d ago

Role: Data Scientist

Location: Bellevue, WA (Onsite)

Position Type : Contract

JOB DESCRIPTION

Role and responsibilities:

• 7+ years in data science, analytics, or related fields.

• Proven track record of delivering data-driven business solutions and deploying ML models in production.

• Experience leading projects or mentoring junior team members is preferred.

• Strong proficiency in Python, R, or similar programming languages.

• Deep knowledge of machine learning frameworks (Scikit-learn, TensorFlow, PyTorch, XGBoost).

• Expertise in statistical analysis, data visualization, and predictive modeling.

• Experience with SQL, NoSQL databases, and data engineering pipelines.

• Familiarity with cloud platforms (AWS, Azure, GCP) and big data tools (Spark, Hadoop) is a plus.

• Strong analytical thinking, problem-solving skills, and business acumen.

• Excellent communication skills to present technical insights to stakeholder

Analyze complex datasets to identify trends, patterns, and business opportunities.

• Build, validate, and deploy machine learning models for predictive, classification, or recommendation purposes.

• Perform feature engineering and data preprocessing to improve model performance.

• Stay up-to-date with emerging techniques in machine learning, deep learning, NLP, and AI.

• Apply advanced statistical and AI methods to solve business challenges.

• Experiment with new algorithms, frameworks, and tools for improved accuracy and scalability.

• Collaborate with Data Engineers and DevOps teams to deploy models into production.

• Monitor model performance, retrain models as needed, and ensure data quality.

• Document model assumptions, limitations, and decision-making processes.

• Work closely with product managers, business stakeholders, and engineering teams to align data science solutions with business needs.

• Mentor junior data scientists and provide technical guidance on modeling, coding, and best practices.

• Present insights and findings to technical and non-technical stakeholders effectively.

• Ensure adherence to data governance, privacy, and compliance policies.

• Address ethical considerations in AI and data modeling.

Best Regards,

Bismillah Arzoo (AB)

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