Lead - Data Scientist

Why would you like to join us?

TransOrg Analytics specializes in Data Science, Data Engineering and Generative AI, providing advanced analytics solutions to industry leaders and Fortune 500 companies across India, US, APAC and the Middle East. We leverage data science to streamline, optimize, and accelerate our clients' businesses. Visit at www.transorg.com to know more about us.

What do we expect from you?

• Analyze & interpret data and communicate results to clients, often with the aid of mathematical/statistical techniques and software.
• Data exploration, statistical/ predictive modelling, data analysis and hypothesis testing. Design, development and deployment of Predictive models and frameworks.
• Complex statistical concepts are explained in a way that clients can understand and advice on strategy.
• Overall data analytics strategy and business development.
• Responsible for providing thought leadership and support to the team to develop best in class analytics solutions for clients.
• Responsible for managing existing relationships with multiple clients in various industries.
• Responsible for working closely with the senior management in developing and implementing strategic plans.
  

Responsibilities:

Project Delivery

• Provide data science and AI expertise to design, build, and deliver scalable ML and deep learning solutions.
• Work extensively with tabular data to develop predictive models, perform feature engineering, and optimize performance for real-world applications.
• Apply conventional machine learning techniques (e.g., regression, classification, ensemble methods) alongside advanced deep learning methods.
• Build and optimize deep learning models for structured and unstructured data, including text and audio.
• Lead development of solutions for audio data, including classification, recognition, and signal processing tasks.
• Design, fine-tune, and deploy LLMs (Large Language Models), SLMs (Small Language Models), and other Generative AI solutions for diverse business applications.
• Translate business problems into well-structured ML/AI problems and deliver actionable insights.
• Deploy production-grade models with a focus on efficiency, scalability, and maintainability.
• Collaborate with cross-functional teams including product managers, engineers, and domain experts to deliver high-impact projects.
• Mentor junior data scientists and interns, fostering innovation and best practices.
• Lead analytics engagements and responsible for delivering the analytics solutions required across multiple clients & projects.
• Provide thought leadership in a number of areas, including predictive modeling, customer segmentation, reporting & analysis, data processing and cleansing.
• Demonstrate strong functional expertise by providing content leadership on projects.
  

Team Development

• Manage and lead a team of Data Scientists, providing direction, coaching, and mentoring for professional growth.
• Drive group development by building expertise in new domains, improving processes, and ensuring productivity, utilization, and quality.
• Develop and deliver training modules to enhance team skills and capabilities.

What are we looking for?

• Bachelors in computer science/ engineering, Statistics, Math or any other relevant degree.
• 5-9 years of relevant experience in Data Science/ML/AI.
• Experience on multiple modeling techniques -Logistic Regression, Linear Regression, Random Forest, Boosting, Neural Networks etc.
• Experience with data visualization tools like Tableau or Power BI.
• Experience of Team, client and stakeholder management.
• Experience in working with unstructured data and text analytics.
• Experience in data mining and data analysis.
• Proven expertise working with large-scale tabular data and building machine learning models.
• Strong knowledge of conventional ML algorithms (tree-based models, SVMs, clustering, etc.).
• Hands-on experience with deep learning frameworks such as TensorFlow / PyTorch.
• Mandatory expertise in LLMs, SLMs, and Generative AI, including fine-tuning, prompt engineering, and deployment.
• Proficiency in Python and libraries such as scikit-learn, pandas, NumPy and SQL.
• Exposure to model deployment frameworks and tools (ONNX, Triton, TensorRT, FastAPI, etc.).
• Familiarity with cloud platforms (Azure/GCP) for training and deploying ML solutions.
• Experience with Databricks is a plus.
• Strong understanding of MLOps practices, reproducibility, and model monitoring.
• Track record of managing data project delivery including ability to meet deadlines, overcome challenges, manage stakeholder expectations, and produce clear deliverable
• Strong problem-solving skills with a keen attention to detail. Ability to think critically and provide data-backed insights.
• Excellent communication skills, both verbal and written.
• Understanding of Cloud Platforms (e.g. Azure / AWS/GCP) and ability to use them for developing, training and testing deep learning models ( good to have)
• Familiarity with cloud-based data warehousing platforms (snowflake) ( good to have)