Data Scientist

We are looking for a highly motivated and skilled Data Scientist to join our growing team. The ideal candidate should possess a robust background in data science, machine learning, and statistical analysis, with a passion for uncovering insights from complex datasets. This role demands hands-on experience in Python and various ML libraries, strong business acumen, and effective communication skills for translating data insights into strategic decisions.

• Develop, implement, and optimize machine learning models for predictive analytics and business decision-making.

• Work with both structured and unstructured data to extract valuable insights and patterns.

• Leverage Python and standard ML libraries (NumPy, Pandas, SciPy, Scikit-Learn, TensorFlow, PyTorch, Keras, Matplotlib) for data modeling and analysis.

• Design and build data pipelines for streamlined data processing and integration.

• Conduct Exploratory Data Analysis (EDA) to identify trends, anomalies, and business opportunities.

• Partner with cross-functional teams to embed data-driven strategies into core business operations.

• Create compelling data stories through visualization techniques to convey findings to non-technical stakeholders.

• Stay abreast of the latest ML/AI innovations and industry best practices.

• 5 years of proven experience in data science and machine learning.

• Proficient in Python and key data science libraries.

• Experience with ML frameworks such as TensorFlow, Keras, or PyTorch.

• Strong understanding of SQL and relational databases.

• Solid grounding in statistical analysis, hypothesis testing, and feature engineering.

• Familiarity with data visualization tools like Matplotlib, Seaborn, or Plotly.

• Demonstrated ability to work with large datasets and solve complex analytical problems.

• Excellent communication and data storytelling skills.

• Knowledge of Marketing Mix Modeling is a plus.

• Hands-on experience with cloud platforms like AWS, Azure, or GCP.

• Exposure to big data technologies such as Hadoop, Spark, or Databricks.

• Familiarity with NLP, computer vision, or deep learning.

• Understanding of A/B testing and experimental design methodologies.