Data Scientist

Summary

OVA.Work is seeking a motivated Data Scientist to analyze complex datasets, build predictive models, and generate actionable insights that support business decisions. The ideal candidate will have a strong foundation in statistics, machine learning, data analysis, and programming, with the ability to translate data into meaningful business outcomes.

Responsibilities

• Collect, clean, and analyze structured and unstructured data from multiple sources
• Develop, train, evaluate, and deploy machine learning models
• Perform exploratory data analysis (EDA) and identify trends, patterns, and anomalies
• Build predictive and statistical models to solve business problems
• Create dashboards, reports, and visualizations to communicate insights
• Collaborate with data engineers, software developers, product managers, and business stakeholders
• Optimize model performance and monitor production models
• Conduct A/B testing and statistical analysis to measure business impact
• Document methodologies, experiments, and model performance
• Stay updated with advancements in AI, machine learning, and data science

Skills

• Strong proficiency in Python or R for data analysis and machine learning
• Experience with SQL and database querying
• Knowledge of machine learning algorithms, statistical modeling, and predictive analytics
• Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or XGBoost
• Familiarity with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn
• Understanding of feature engineering, model evaluation, and model deployment
• Knowledge of cloud platforms (AWS, Azure, or Google Cloud) is an advantage
• Familiarity with Git and version control
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
• 2–5+ years of experience in data science, machine learning, or analytics (depending on the role level)
• Strong analytical, problem-solving, and critical-thinking skills
• Excellent communication and presentation abilities
• Experience with MLOps tools and model deployment pipelines
• Knowledge of big data technologies such as Spark or Hadoop
• Familiarity with NLP, computer vision, recommendation systems, or time-series forecasting
• Experience working in Agile/Scrum environments
• Contributions to open-source projects, research publications, or data science competitions are a plus

Qualifications

Must Haves

• Strong proficiency in Python or R for data analysis and machine learning
• Experience with SQL and database querying
• Knowledge of machine learning algorithms, statistical modeling, and predictive analytics
• Experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or XGBoost
• Familiarity with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn
• Understanding of feature engineering, model evaluation, and model deployment
• Knowledge of cloud platforms (AWS, Azure, or Google Cloud) is an advantage
• Familiarity with Git and version control
• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field
• 2–5+ years of experience in data science, machine learning, or analytics (depending on the role level)
• Strong analytical, problem-solving, and critical-thinking skills
• Excellent communication and presentation abilities

Nice to Haves

• Experience with MLOps tools and model deployment pipelines
• Knowledge of big data technologies such as Spark or Hadoop
• Familiarity with NLP, computer vision, recommendation systems, or time-series forecasting
• Experience working in Agile/Scrum environments
• Contributions to open-source projects, research publications, or data science competitions are a plus

Benefits

• Health insurance
• Flexible work arrangements
• Learning and development opportunities
• Performance-based incentives
• Paid time off