Data Scientist

About Qwerky AI

QWERKY AI is a human-centered artificial intelligence company focused on building practical and approachable AI tools for real-world use. Headquartered in Columbia, South Carolina, with a distributed team across the U.S., QWERKY is led by a founding team of tech entrepreneurs with over a decade of experience. The company is dedicated to creating AI that enhances — rather than replaces — human intelligence. QWERKY AI is currently developing an AI platform to empower knowledge workers, creatives and small businesses.

Job Description

QWERKY AI seeks an experienced and innovative Data Scientist to join our dynamic Research & Development team. In this role, you will leverage your expertise to tackle complex business challenges, drive data-informed strategies, and develop sophisticated machine learning models. The ideal candidate is a proactive problem-solver with a proven track record of delivering impactful data science solutions from conception to deployment. You will play a key role in shaping our data science initiatives, working on end-to-end projects, and collaborating with a talented team of engineers and researchers.

Responsibilities

• Assist in the design, development, and implementation of advanced machine learning models and statistical analyses to address complex business problems.
• Take ownership of a data science experiment through the entire lifecycle: from problem definition/hypothesis, data acquisition and exploration, feature engineering, and model selection to deployment, monitoring, and iteration.
• Conduct in-depth exploratory data analysis (EDA) to identify significant trends, extract actionable insights, and formulate hypotheses.
• Develop robust and scalable data science experiments and code.
• Effectively communicate complex analytical results, insights, and recommendations to diverse audiences, including technical peers and non-technical stakeholders, through clear visualizations and compelling narratives.
• Collaborate closely with cross-functional teams (e.g., engineering, product, operations) to define experiment requirements, experiment with data science solutions, and help drive business value.
• Stay at the forefront of advancements in data science, machine learning, and artificial intelligence; evaluate and introduce new technologies and methodologies to the team.
• Ensure rigor in independent experiment design, model validation, evaluation, and testing.
• Contribute to the development of best practices for data science and experimentation.

Required Skills

• Bachelor's, Master's, or PhD in Data Science, Computer Science, Statistics, Mathematics, Physics, Engineering, or a related quantitative field.
• Proven experience (typically 3- 5+ years) in applying data science and machine learning techniques to solve real-world problems.
• Deep understanding of statistical modeling, machine learning algorithms (e.g., backpropagation, regression, classification, clustering, ensemble methods, time series analysis, NLP techniques), and their underlying mathematical principles.
• Strong proficiency in Python for data science, including extensive experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, Matplotlib, and Seaborn. Proficiency in at least one language relevant to GPUs or Accelerators (e.g., C++).
• Demonstrated experience in the end-to-end model development lifecycle, including data collection, preprocessing, feature engineering, model training, validation, and deployment.
• Proficiency in SQL and experience working with relational databases; familiarity with NoSQL databases is a plus.
• Excellent analytical, critical thinking, and problem-solving abilities with a strong data-driven mindset.
• Ability to clearly and effectively communicate complex technical concepts and results to technical and non-technical audiences.
• Experience in leading experiments or experimental components and working autonomously with minimal supervision.
• Track record of delivering high-impact data science solutions.

Bonus Skills

• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) in applied settings.
• Understanding of MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes).
• Strong experience with cloud computing platforms (e.g., AWS, Azure, GCP) and their associated machine learning services.
• Experience with big data technologies (e.g., Spark, Hadoop, Dask, Kafka).
• Published research in relevant AI/ML conferences or journals.
• Expertise in a specialized area such as Natural Language Processing (NLP), Computer Vision, Reinforcement Learning, or Recommender Systems.
• Knowledge of C++ for performance-critical applications.
• Familiarity with parallel computing and distributed computing.
• Exposure to CUDA programming for GPU acceleration.
• Understanding of GPU kernels and their optimization.
• Contributions to open-source data science projects.

Pay / Benefits

• Salary or hourly rate
• Stock options plan (we are a private company, so this is not liquid) 
• If you are in the USA: healthcare, dental, vision, 401k 
• Unlimited time off policy
• Flexible working hours

Hiring Process

• Submit a resume to us for review.
• We will follow up with a technical screening (this will take approximately one hour)
• Following the successful completion of the technical screening, we will schedule an Onsite Interview
• The Onsite Interview to meet more of the team, it will consist of the following (total time three hours):
• • Technical Screenings (1-2)
  • System Design
  • Behavioral Interview
• We’ll reach out with an offer if you're a great fit. 
• Once accepted, you start working with us!