Applied Scientist, Remote- Contract Remote (International)

Dover; India; Remote; INR 3.271.000 - 7.850.000; Teilzeit

Zusammenfassung

Dover is seeking an Applied Scientist contractor to join a remote team working on live AI projects. You will design experiments, build ML models, and deliver reproducible analyses with clear documentation. Strong Python, Pandas, and data modeling skills, plus solid statistical thinking, are essential.

Collaborative communication and a practical, results-driven mindset are valued in this flexible, remote role. No prior AI experience is required; your domain knowledge matters.

Qualifikationen

• Proficient in Python with Pandas and scikit-learn (sklearn).
• Experience in applied statistics, experimental design and ML.
• Able to develop, tune and evaluate ML models in practical settings.
• Strong data modeling skills for structured and unstructured data.

Aufgaben

• Design and execute statistical analyses to uncover insights from complex datasets.
• Develop and validate machine learning models for business or research objectives.
• Apply data modeling techniques and manage large-scale data transformations with Python and Pandas.
• Collaborate with stakeholders to define experimentation frameworks and analyze outcomes.
• Document methodology, findings and recommendations with clarity and precision.
• Deliver reproducible code and analytical reports as part of project deliverables.
• Evaluate AI model outputs on statistics, ML, experimentation, and quantitative problems.
• Create expert prompts, datasets, and reference solutions.
• Provide constructive feedback to improve model capability.

Kenntnisse

Python

Machine Learning

Statistics

Data Analysis

Experimentation

Pandas

Data Modeling

Ausbildung

Advanced degree in data science or related field

Jobbeschreibung

Role Title:

Applied Scientist

Role Type:

Contractor

Location:

Remote

Required Skills:

• Python
• Machine Learning
• Statistics
• Data Analysis
• Experimentation
• Pandas
• Data Modeling

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required; your domain knowledge is what matters. This opportunity is part of an open Data Scientist project, with a strong emphasis on clear written and verbal communication.

Scope of Work:

• Design and execute statistical analyses to uncover actionable insights from complex datasets.
• Develop and validate machine learning models for various business or research objectives.
• Apply data modeling techniques and manage large-scale data transformations using Python and Pandas.
• Collaborate with stakeholders to define experimentation frameworks and analyze outcomes.
• Document methodology, findings, and recommendations with a focus on clarity and precision.
• Review peer contributions and provide high-quality feedback to support knowledge sharing.
• Deliver reproducible code and well-organized analytical reports as part of the project deliverables.
• Evaluate AI model outputs on statistics, machine learning, experimentation, and quantitative problems.
• Create expert-level prompts, datasets, and reference solutions.
• Identify flawed methodology, statistical errors, and weak quantitative reasoning.
• Provide clear, structured feedback that improves model capability.

Preferred Qualifications:

• At least one year at a top company (tech, finance, or research).
• Expertise in Python, including proficiency with libraries such as Pandas and scikit-learn (sklearn).
• Demonstrated experience in applied statistics, experimental design, and machine learning.
• Proven ability to develop, tune, and evaluate machine learning models in practical settings.
• Strong data modeling skills and experience managing structured and unstructured data.
• Excellent written and verbal communication skills, with a passion for clear technical documentation.
• Experience collaborating on open or cross-functional data science projects is a plus.
• Advanced academic background or hands-on work in data science, applied mathematics, or related fields.