Strong Problem-Solving Skills Jobs in Remote

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Looking for Strong Problem-Solving Skills jobs in Remote? Browse our curated listings with transparent salary information to find the perfect Strong Problem-Solving Skills position in the Remote area.

Technical Support Representative: Service Desk

Company: Kyndryl

Location: Alajuela, Costa Rica / Remote

Posted Feb 07, 2025

Global Benefits Program Specialist

Company: Equinix, Inc

Location: Manila, Philippines / Remote

Posted Feb 07, 2025

Art Producer, Metaverse

Company: Meta

Location: Remote

Posted Feb 07, 2025

Multifamily Foreperson

Company: Sunrun

Location: Remote

Posted Feb 07, 2025

Frequently Asked Questions

What are typical salary ranges by seniority for problem‑solving roles?
Entry‑level (0‑2 yrs): $70k‑$90k; Mid‑level (3‑5 yrs): $90k‑$125k; Senior (6‑10 yrs): $125k‑$180k; Lead/Principal: $180k‑$250k+.
Which skills and certifications are required for strong problem‑solving professionals?
Core stack: Python, SQL, R; data viz: Tableau, PowerBI; modeling: scikit‑learn, TensorFlow, PyTorch; process optimization: Six Sigma Green Belt; cloud: AWS Certified Solutions Architect, Google Cloud Professional Data Engineer; dev‑ops: Docker, Kubernetes; security: CompTIA Security+, CEH.
How common is remote or hybrid work in problem‑solving positions?
Over 80% of listings support full‑remote or hybrid arrangements, with most companies providing cloud‑based dev environments and flexible hours. Remote roles emphasize strong communication and self‑management.
What career progression paths exist for problem‑solving specialists?
Typical path: Junior Analyst → Analyst → Senior Analyst → Lead Analyst → Manager → Director of Analytics → VP of Data Science. For software roles: Junior Dev → Developer → Senior Dev → Tech Lead → Engineering Manager → VP of Engineering.
What industry trends are shaping demand for problem‑solving talent?
Automated ML pipelines, AI‑driven decision systems, edge‑computing analytics, and ethical AI governance are driving demand for roles that can architect reproducible ML workflows and enforce data governance.

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