AI/ML & Data Science Lead
- Synechron
- 7 - 12 years
- Bengaluru
- 1 month ago
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Job Description
Job Summary
Synechron is seeking a skilled AI/ML Data Scientist to lead data-driven projects that develop innovative solutions across diverse industries. This role involves designing and implementing machine learning models, deep learning architectures, and NLP solutions to solve complex business problems. The Data Scientist will collaborate with cross-functional teams to translate data insights into actionable strategies, stay current with emerging trends, and identify new opportunities for technological and business growth.
Software Requirements
Required:
- Practical experience with programming in Python (including libraries like NumPy, pandas, scikit-learn).
- Experience with ML frameworks such as TensorFlow and PyTorch.
- Strong knowledge of SQL for data extraction and management.
- Familiarity with data visualization tools and libraries such as Matplotlib, Seaborn, or Plotly.
- Solid understanding of machine learning algorithms, deep learning, NLP, and computer vision.
- Ability to work with large datasets, perform feature engineering, and model validation.
Preferred:
- Experience with R for statistical analysis.
- Proficiency with cloud platforms like AWS (S3, SageMaker, Lambda), Azure, or GCP.
- Knowledge of MLOps platforms and tools (e.g., MLflow, Kubeflow).
- Experience in deploying models in production environments.
Overall Responsibilities
- Lead the design, development, and deployment of AI/ML models to address business challenges and innovate operational processes.
- Collaborate with cross-functional teams including product managers, engineers, and business stakeholders to define requirements and translate data insights into solutions.
- Mentor and guide junior team members in best practices for model development, evaluation, and deployment.
- Evaluate emerging technological trends, such as NLP, computer vision, or reinforcement learning, and recommend their application to business problems.
- Develop scalable, automated, and production-ready AI solutions using best practices in model validation, versioning, and monitoring.
- Communicate complex technical concepts to non-technical audiences and present data-driven insights effectively.
- Monitor and improve model performance over time, ensuring robustness and fairness.
Performance outcomes: Consistently deliver impactful AI/ML solutions that improve operational efficiency, decision-making, or customer experience, while ensuring model accuracy, fairness, and compliance with data privacy standards.
Technical Skills (By Category)
Programming Languages:
- Essential: Python, SQL
- Preferred: R, Java, or Scala for scalable data processing and analytics.
Data Model Management:
- Expertise with data preprocessing, feature engineering, and model validation techniques.
- Knowledge of model versioning and deployment practices.
Cloud Technologies:
- Preferred: AWS (S3, SageMaker, Lambda), Azure, GCP
Frameworks Libraries:
- Essential: TensorFlow, PyTorch, scikit-learn, NLTK, SpaCy
- Preferred: Keras, OpenCV for computer vision tasks.
Development Tools Methodologies:
- Essential: Jupyter Notebooks, Git, CI/CD pipelines, Agile practices
- Preferred: MLflow, Kubeflow, Docker, Kubernetes
Security Compliance:
- Understanding of privacy-preserving techniques, GDPR, and data security standards.
Experience Requirements
- 7+ years of experience in AI/ML project development, including model design, evaluation, and deployment.
- Proven track record of delivering end-to-end AI/ML solutions in production environments.
- Experience working with large datasets, performing advanced analytics, and implementing NLP or computer vision models.
- Demonstrated ability to mentor team members and lead technical initiatives.
- Industry experience in finance, healthcare, retail, or technology sectors is preferred; relevant experience supporting business transformation initiatives is acceptable.
Day-to-Day Activities
- Design, develop, and validate machine learning models addressing defined business use cases.
- Collaborate with product and engineering teams to deploy models into production environments efficiently.
- Conduct feature engineering, hyperparameter tuning, and model evaluation to ensure optimal performance.
- Monitor deployed models, retrain and improve them based on feedback and new data.
- Contribute to data collection, labeling, and preprocessing pipelines.
- Share insights and model results through presentations and reports tailored for diverse audiences.
- Stay updated on latest research, tools, and techniques, proposing innovative solutions.
Qualifications
- Bachelors or Masters degree in Data Science, Computer Science, or related fields; PhD preferred.
- 7+ years of experience developing AI/ML models, with a strong portfolio of projects.
- Relevant certifications (e.g., TensorFlow Developer, AWS Certified Machine Learning) are advantageous.
- Proven ability to lead projects, mentor team members, and work collaboratively.
- Excellent communication skills for articulating technical insights to stakeholders.
Professional Competencies
- Critical thinking and advanced problem-solving for complex data science challenges.
- Leadership and mentorship, fostering team growth and knowledge sharing.
- Clear communication, able to translate technical concepts into business language.
- Curiosity and eagerness to stay current with emerging AI research and tools.
- Ownership mindset, delivering high-quality, ethical, and impactful AI solutions.
- Effective time management, balancing multiple projects and priorities effectively.
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Data Science & AnalyticsRole Category: Data Science & Machine LearningRole: Data Science & Machine Learning - OtherEmployement Type: Full timeContact Details:
Company: SynechronLocation(s): Bengaluru+ View Contact
Keyskills: python kubernetes scala nltk numpy sql docker cloud deep learning tensorflow java git seaborn data science pytorch data scientist keras ml ai cloud platforms machine learning pandas r compliance matplotlib agile finance
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