We are seeking a motivated and analytical Data Scientist with experience in developing data-driven solutions. The ideal candidate will have a solid foundation in statistics, machine learning, data analysis, and programming, with the ability to derive actionable insights from data and contribute to building predictive models that address business challenges.
Key Responsibilities
- Collect, clean, and preprocess structured and unstructured data from multiple sources.
- Perform exploratory data analysis (EDA) to identify trends, patterns, and business insights.
- Build, train, evaluate, and optimize machine learning models under the guidance of senior team members when required.
- Apply statistical techniques to analyze data and support business decision-making.
- Assist in developing predictive models and collaborate with engineering teams to support model deployment.
- Work closely with business stakeholders, product managers, and data engineers to understand requirements and translate them into analytical solutions.
- Create dashboards, reports, and visualizations to effectively communicate findings and recommendations.
- Monitor model performance, identify potential improvements, and support model maintenance activities.
- Assist in designing and analyzing A/B tests and other statistical experiments.
- Write efficient, maintainable, and well-documented Python and SQL code for data processing and analysis.
- Document methodologies, experiments, and model outcomes to support knowledge sharing and reproducibility.
- Stay up to date with emerging trends and best practices in Data Science, Machine Learning, and Artificial Intelligence.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
- 2+ years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics.
- Strong proficiency in Python and SQL.
- Experience with data manipulation and analysis libraries such as Pandas and NumPy.
- Hands-on experience with machine learning libraries such as Scikit-learn, XGBoost, TensorFlow, or PyTorch.
- Good understanding of statistics, probability, hypothesis testing, and model evaluation techniques.
- Experience creating visualizations using Power BI, Tableau, Matplotlib, or Seaborn.
- Familiarity with relational databases such as MySQL or PostgreSQL; basic knowledge of NoSQL databases is a plus.
- Basic understanding of cloud platforms (AWS, Azure, or Google Cloud Platform) is desirable.
- Experience using Git or other version control systems.
- Strong analytical, problem-solving, communication, and collaboration skills.
Pay: $101,690.19 - $121,895.71 per year
Benefits:
- 401(k)
- Dental insurance
- Flexible schedule
- Health insurance
- Paid time off
Work Location: In person
