Data Scientist

Job Title: Data Scientist (Mid-Level)

Location: remote

Salary: $55 — $65 per hour (W2)

Projected Total Compensation: Approximately $114,400 — $135,200 annually (based on 40-hour workweek)

Start: ASAP

About the Role (Summary of project)

Gentis Solutions is seeking a Mid-Level Data Scientist to join our Professional Consultants group. In this role, you will work with business leaders, technical stakeholders, and cross‑functional teams to design and implement advanced data science solutions leveraging machine learning, natural language processing, deep learning, unstructured data processing, and large language models (LLMs).

This position requires strong analytical thinking, independence, and adaptability, especially when working with ambiguous or evolving business requirements. You will be responsible for building predictive models, developing analytical solutions, and communicating insights that drive high‑impact decision‑making.

What You’ll Do (Job Description) Strategic Collaboration

• Partner with business leaders to understand needs and translate them into data‑driven goals, project scopes, and success metrics.

Requirements Gathering & Project Execution

• Independently gather requirements, assess data readiness, build project plans, manage timelines, and deliver results with minimal supervision.

Advanced Analytics & Modeling

• Conduct data mining on structured and unstructured datasets
  .
• Build, evaluate, and maintain predictive models using ML, NLP, DL, and LLM techniques.

Solution Deployment & Monitoring

• Collaborate with engineering and cross‑functional teams to deploy models into production.
• Develop and maintain monitoring processes to ensure model accuracy and data integrity.

Communication & Reporting

• Present findings to both technical and non‑technical audiences in clear, actionable terms.
• Document processes, insights, and model behavior for transparency and reproducibility.

Team Collaboration

• Participate actively in team meetings, share knowledge, and stay updated on data science trends and emerging technologies.

What We’re Looking For (Must Haves)

• Experience with unstructured data processing.
• Experience using Large Language Models (LLMs).
• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or a related field (Master’s preferred but not required).
• 3–5 years of relevant data science experience (advanced degrees may substitute).
• Proficiency in Python or R.
• Hands‑on experience in machine learning
  , statistical modeling
  , NLP
  , and deep learning
  .
• Experience working with large datasets
  , preprocessing, and feature engineering.
• Strong understanding of business domains such as life insurance or similar industries
  .
• Ability to independently manage full project life cycles: scoping → planning → execution → communication.
• Strong written and verbal communication skills.

Preferred (Nice‑to‑Have Skills)

• Master’s or PhD in a relevant field.
• Prior experience in life insurance or related industries.
• Publications
  , patents, or research contributions.
• Familiarity with software engineering practices
  , version control, or deployment pipelines.
• Certifications such as AWS ML Specialty or Google Professional Data Engineer
  .
• Proven success collaborating within cross‑functional teams.

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