Responsibilities:

1. Collaborate with cross-functional teams to understand business objectives and formulate data-driven solutions.

2. Collect, clean, and preprocess large datasets to prepare them for analysis.

3. Apply statistical analysis and machine learning techniques to develop predictive models and uncover patterns within the data.

4. Build and deploy machine learning models into production environments.

5. Conduct exploratory data analysis (EDA) to discover trends, patterns, and anomalies in the data.

6. Communicate complex technical findings to both technical and non-technical stakeholders through data visualizations and reports.

7. Collaborate with IT teams to integrate and implement model outputs into business processes.

8. Stay current with industry trends and advancements in data science, machine learning, and artificial intelligence.

Qualifications:

1. Master's or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.

2. Proven experience as a Data Scientist or in a similar role.

3. Strong programming skills in languages such as Python or R.

4. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).

5. Proficiency in working with large datasets and databases (SQL, NoSQL).

6. Strong statistical analysis skills and a solid understanding of statistical modeling techniques.

7. Ability to translate business problems into analytical solutions and present findings to non-technical stakeholders.

8. Excellent problem-solving skills and attention to detail.

Nice to Have:

1. Experience with big data technologies (Hadoop, Spark).

2. Familiarity with data visualization tools (Tableau, Power BI).

3. Knowledge of natural language processing (NLP) and text analytics.

4. Experience with cloud platforms (e.g., AWS, Azure, GCP).