Data and AI PH – Associate Manager Data Scientist

Strategic & Leadership Responsibilities

• Lead end-to-end data science projects from problem definition to deployment and monitoring.
• Business Analysis: Translate business challenges into data science problems and propose optimal solutions.
• Mentor junior data scientists and analysts, fostering a culture of continuous learning and experimentation.
• Collaborate with stakeholders aligning data science initiatives with strategic goals.
• Provides advisory and consultation services to determine the right solution
• Participates in Technical/Work product Reviews

• Contributes to knowledge tools and communities, and ensures project learnings are documented and shared.
• Knowledge sharing and re-use within practice or profession.
• Mentors junior team members, providing technical assistance and constructive feedback.

Technical Responsibilities

• Design, develop, and validate predictive models, classification algorithms, and other data science assets using statistical and machine learning techniques.
• Perform exploratory data analysis, feature engineering, and model tuning to improve performance.
• Build scalable data pipelines and integrate models into production environments in collaboration with data engineering and MLOps teams.
• Evaluate model performance using appropriate metrics and ensure robustness, fairness, and explainability.
• Stay current with advancements in AI/ML and recommend adoption of relevant technologies and methodologies.

Operational Responsibilities

• Document methodologies, workflows, and model assumptions for transparency and reproducibility.

• Ensure compliance with data governance, privacy, and ethical AI standards.

Qualifications & Experience

Education and Experience:

• 5+ years of professional experience as a Data Scientist/ AI/ML Engineer and a Bachelor of Arts/Science or equivalent degree in computer science or related area of study; without a degree, three additional years of relevant professional experience (8+ years in total).
• Proven track record of delivering impactful data science solutions in enterprise environments.
• Experience working with large-scale structured and unstructured data.

Technical Skills

• Proficiency in Python, R, SQL, and relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, XGBoost).
• Strong understanding of statistical modeling, machine learning, deep learning, NLP, GenAI
• Experience with cloud platforms (Preferred: Azure, GCP, AWS ) specifically cloud-based AI/ML tools and containerization tools (Docker, Kubernetes).
• Experience with LLMs, RAG, LangChain, Generative AI
• Knowledge of data visualization tools (Power BI, Tableau, Plotly).
• Familiarity with MLOps practices and tools (MLflow, Airflow, CI/CD pipelines).

Soft Skills

• Strong problem-solving and critical thinking abilities.
• Ability to manage multiple projects and prioritize effectively.
• Collaborative mindset with a proactive approach to stakeholder engagement.
• Excellent communication and storytelling skills to convey complex insights to non-technical stakeholders.
• Strong time management practice, able to prioritize project demands within the allocated time.
• Champion of continuous learning

Preferred Certifications

• Microsoft Certified: Azure Data Scientist Associate or Azure AI Engineer Associate
• Google Professional Machine Learning Engineer
• AWS Certified Machine Learning

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