Job Title: Data Scientist II / Mid-Level Data Scientist

About the Role

We are looking for an experienced and analytical Data Scientist II to join our data science team. In this role, you will take ownership of data-driven projects, from exploratory analysis to model development and deployment. You will collaborate with cross-functional teams to solve business challenges and unlock insights through machine learning, advanced analytics, and scalable data solutions.

This is an exciting opportunity for professionals who have hands-on experience in data science and want to deepen their technical expertise while contributing directly to impactful business outcomes.

Key Responsibilities

• Design, build, and deploy predictive models and machine learning algorithms to support key business initiatives
• Conduct data exploration, feature engineering, and model evaluation to deliver robust analytical solutions
• Work with cross-functional teams including product, marketing, and operations to translate business questions into analytical problems
• Analyze large and complex datasets using statistical and machine learning techniques
• Optimize model performance for accuracy, interpretability, and scalability
• Generate actionable insights and provide data-driven recommendations to influence strategic decision-making
• Present analytical results to both technical and non-technical stakeholders through clear storytelling and visualization
• Document workflows, methodologies, and findings for reproducibility and team knowledge sharing
• Stay current with the latest tools, libraries, and trends in data science and machine learning

Required Qualifications

Education:

• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or a related quantitative discipline
• Master’s degree preferred and considered a strong advantage

Experience:

• 2–4 years of professional experience as a Data Scientist or in a similar analytics role

Technical Skills & Tools

• Programming: Strong proficiency in Python or R, with experience in libraries such as pandas, NumPy, scikit-learn, XGBoost, LightGBM
• SQL: Advanced SQL skills for querying and manipulating large-scale data from relational databases
• Cloud Platforms: Hands-on experience with AWS, Google Cloud Platform (GCP), or Azure for data and model operations
• Big Data Tools: Familiarity with Apache Spark, Hive, or similar tools for handling distributed data
• Machine Learning: Solid understanding of supervised and unsupervised learning, model validation, and performance tuning
• Data Visualization: Proficiency with data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI)
• Version Control & Workflow: Experience using Git, Jupyter Notebooks, and basic ML workflow orchestration (e.g., Airflow, MLflow)

Soft Skills & Competencies

• Strong analytical and critical thinking skills with a problem-solving mindset
• Ability to communicate complex technical findings to non-technical audiences
• Proactive, self-directed, and comfortable working independently or in collaborative settings
• Strong business acumen and ability to connect data work to business value

Preferred Qualifications (Nice to Have)

• Experience working with real-time data or streaming analytics
• Exposure to model deployment, containerization (Docker), or API integration
• Knowledge of A/B testing, causal inference, or time series forecasting
• Familiarity with data governance, ethics in AI, or responsible ML practices