Associate Director - Data Scientist

Role Overview We are looking for a skilled and innovative Data Scientist with a minimum of 5 years of professional experience. The ideal candidate will have a strong analytical mindset, advanced technical expertise, and a proven ability to extract meaningful insights from large and complex datasets. You will play a critical role in driving data-driven decisions, building predictive models, and enabling scalable data solutions to support our business objectives. Key Responsibilities 

• Analyze complex datasets to uncover actionable insights, trends, and opportunities for optimization. 
• Design and implement analytical frameworks to solve business challenges. 
• Develop, train, and deploy predictive and prescriptive models using machine learning and statistical techniques. 
• Continuously improve model performance and scalability. 
• Collaborate with data engineering teams to ensure the availability and quality of data pipelines. 
• Implement data preprocessing, transformation, and feature engineering processes. 
• Work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to align data initiatives with organizational goals. 
• Translate business problems into data science tasks and communicate results effectively to non-technical stakeholders. 
• Leverage advanced data science tools and frameworks for statistical analysis, machine learning, and data visualization. 
• Stay updated on emerging technologies and incorporate best practices in data science workflows. 
• Define and track key metrics to measure the success of models and business impact. 
• Conduct A/B testing and experiments to validate hypotheses and model effectiveness. 

Qualifications Education: 

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Data Science, or a related field. A PhD is a plus. 

Experience: 

• At least 3-5 years of hands-on experience in data science, machine learning, or a related role. 
• Proven experience in deploying models in production environments. 

Technical Skills: 

• Proficiency in programming languages such as Python, R, or Java. 
• Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). 
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn). 
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure, GCP). 
• Expertise in working with SQL and NoSQL databases. 

Preferred Qualifications: 

• Experience in natural language processing (NLP), computer vision, or deep learning. 
• Knowledge of CI/CD pipelines and MLOps best practices. 
• Certification in data science, machine learning, or cloud computing (e.g., AWS Certified Data Analytics, Microsoft Azure Data Scientist Associate). 

Soft Skills: 

• Strong problem-solving and critical thinking abilities. 
• Excellent communication and storytelling skills to convey insights effectively. 
• Ability to work collaboratively in a fast-paced, cross-functional environment.