Senior Data Scientist

Key Responsibilities:

1. Design, develop, and implement advanced machine learning models to solve complex business problems.
2. Apply AI techniques and generative AI models to enhance data analysis and predictive capabilities.
3. Utilize Tableau and other visualization tools to create insightful and actionable dashboards for stakeholders.
4. Manage and optimize large datasets using Snowflake and Teradata databases.
5. Collaborate with cross-functional teams to understand business needs and translate them into analytical solutions.
6. Stay updated with the latest advancements in data science, machine learning, and AI technologies.
7. Mentor and guide junior data scientists, fostering a culture of continuous learning and development.
8. Communicate complex analytical concepts and results to non-technical stakeholders effectively.

Key Technologies & Skills:

1. Machine Learning Models: Supervised learning, unsupervised learning, reinforcement learning, deep learning, neural networks, decision trees, random forests, support vector machines (SVM), clustering algorithms, etc.
2. AI Techniques: Natural language processing (NLP), computer vision, generative adversarial networks (GANs), transfer learning, etc.
3. Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn, Plotly, etc.
4. Databases: Snowflake, Teradata, SQL, NoSQL databases.
5. Programming Languages: Python (essential), R, SQL.
6. Python Libraries: TensorFlow, PyTorch, scikit-learn, pandas, NumPy, Keras, SciPy, etc.
7. Data Processing: ETL processes, data warehousing, data lakes.
8. Cloud Platforms: AWS, Azure, Google Cloud Platform.

Minimum Qualifications:

1. Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Data Science, or a related field.
2. Minimum of [X] years of experience as a Data Scientist or in a similar role.
3. Proven track record in developing and deploying machine learning models and AI solutions.
4. Strong expertise in data visualization tools, particularly Tableau.
5. Extensive experience with Snowflake and Teradata databases.
6. Excellent problem-solving skills and the ability to work independently and collaboratively.
7. Exceptional communication skills with the ability to convey complex information clearly.

Preferred Qualifications (Provide up to five (5) bullet points: these can include soft skills)

1. Excellent communication and collaboration skills to work effectively in cross-functional teams.
2. Ability to translate business requirements into technical solutions.
3. Strong problem-solving skills and the ability to work with complex datasets.
4. Experience in statistical analysis and machine learning techniques.
5. Understanding of business domains such as sales, financials, marketing, and telemetry.