Role Overview
We are seeking passionate and talented Data Scientists of all experience levels to join our growing team. As a Data Scientist at Starnet AI, you will be instrumental in driving our business forward by uncovering insights and building intelligent products from our vast datasets. You will collaborate with a multidisciplinary team of engineers, product managers, and business leaders to tackle challenging problems and create significant value for our clients. This role offers a unique opportunity to grow your skills and make a tangible impact, whether you are starting your career or are a seasoned professional.
Key Responsibilities
Data Analysis & Insights: Collect, clean, and perform exploratory data analysis on large, complex datasets to identify actionable trends, patterns, and insights.
Modeling: Design, develop, validate, and deploy machine learning models to address business challenges such as prediction, classification, clustering, and optimization. Junior members will assist in these tasks, while senior members will lead model architecture and strategy.
End-to-End Projects: Participate in the full data science project lifecycle, from problem formulation and data acquisition to model deployment and performance monitoring in a production environment.
Collaboration & Communication: Work closely with cross-functional teams to understand business requirements and effectively communicate complex analytical results and insights to both technical and non-technical stakeholders.
Innovation: Stay current with the latest advancements in data science, machine learning, and AI. Contribute to the team's technical capabilities by researching and implementing new tools and methodologies.
Mentorship (for Data Scientist level): Mentor junior team members, providing technical guidance and fostering a culture of learning and continuous improvement.
Qualifications
We are open to candidates with a range of experience and encourage anyone who meets the core qualifications to apply.
Core Qualifications (Applicable to all levels):
A Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or Engineering.
A genuine passion for solving complex problems with data.
Strong programming skills in Python and proficiency with its core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
Solid knowledge of SQL for data querying and manipulation.
A solid foundation in statistical concepts and machine learning principles.
Excellent communication skills and the ability to work effectively in a collaborative team environment.
For Junior Data Scientist Level:
0-2 years of relevant experience (including internships, academic projects, or bootcamps).
Demonstrable experience building projects with data, showcasing your ability to manipulate data and apply fundamental ML algorithms.
An insatiable curiosity and a strong desire to learn and grow your data science skills.
For Data Scientist Level:
3+ years of professional experience in a data science or machine learning role.
A Master’s or PhD is a strong plus.
Proven track record of successfully developing and deploying machine learning models into a production environment.
Deeper experience with advanced ML techniques (e.g., deep learning) and frameworks like TensorFlow or PyTorch.
Experience with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, Google Cloud) is highly desirable.
Demonstrated ability to lead projects and work independently.
