Data Science Lead

This is a fully remote position, open to applicants in India.

📋 Description

• Design and execute both supervised and unsupervised machine learning models (e.g., OLS, Logistic Regression, Ensemble Methods) to address real-world business challenges.

• Spearhead the development of advanced neural network architectures, including ANN, CNN, RNN, GAN, Transformers, and RESNet.

• Propel advancements in natural language processing using tools like NLTK and neural-based language models.

• Supervise the creation of computer vision models, applying OpenCV for practical applications.

• Direct time-series modeling initiatives focused on forecasting and anomaly detection.

• Employ AI techniques such as Retrieval-Augmented Generation (RAG), Chain of Thought (CoT), and Model of Alignment (MOA) to boost model performance.

• Develop and sustain scalable data pipelines for both streaming and batch processing environments.

• Design and refine lakehouse solutions utilizing Delta/Iceberg and bronze-silver-gold architectures.

• Oversee the establishment of ETL processes using tools like Airflow, DBT, and Airbyte to facilitate data flow and transformation.

• Create and enhance database models for OLTP and OLAP systems using Snowflake, SQL Server, PostgreSQL, and MySQL.

• Build NoSQL solutions leveraging MongoDB, DynamoDB, and ElasticSearch for handling unstructured data.

• Lead initiatives in constructing cloud infrastructure, particularly in AWS (preferred) or Azure, utilizing services such as Lambda, API Gateway, Batch processing, Kinesis, and Kafka.

• Manage MLOps pipelines to ensure robust deployment of machine learning models in production environments with platforms like Sagemaker, Databricks, and Azure ML Studio.

• Design and optimize business intelligence dashboards using tools like Tableau, QuickSight, and PowerBI to derive actionable insights.

• Implement GPU acceleration and CUDA for effective model training and optimization.

• Mentor junior team members on innovative AI/ML techniques and best practices.

⛳️ Requirements

• Demonstrated proficiency in both supervised and unsupervised machine learning, advanced deep learning, including experience with TensorFlow, PyTorch, and neural network architectures (e.g., CNN, GAN, Transformers).

• Practical experience with machine learning libraries and tools such as Scikit-learn, Pandas, and Numpy.

• Strong expertise in AI model development using large language model libraries (e.g., Langchain, Huggingface, OpenAI).

• Solid MLOps capabilities, with hands-on experience in deploying scalable production pipelines using tools like Sagemaker, Databricks, and Azure ML Studio.

• Advanced knowledge of big data frameworks such as Apache Spark, Glue, and EMR for distributed model training.

• Strong expertise in ETL processes and data pipeline development using tools like Airflow, DBT, and Airbyte.

• Comprehensive understanding of lakehouse architectures (Delta/Iceberg) and experience with data quality frameworks like Great Expectations.

• Proficiency in cloud platforms (AWS preferred or Azure), with in-depth knowledge of services like IAM, VPC networking, Lambda, API Gateway, Batch, Kinesis, and Kafka.

• Skilled in Infrastructure as Code (IaC) tools such as Terraform or CloudFormation for automation purposes.

• Advanced capabilities in GPU acceleration, CUDA, and distributed model training.

• Proven ability to design and implement scalable machine learning and data-intensive systems.

• Expertise in database modeling for OLTP/OLAP systems and familiarity with both relational and NoSQL databases.

• Strong mentoring abilities, with a history of guiding junior team members in AI/ML best practices.

• Bachelor’s degree in a relevant field (required), with a Master’s or PhD in Data Science or a related discipline (preferred).

• Over 7 years of experience in data science, machine learning, or data engineering.

• AWS or Azure certification (highly preferred).

• Excellent communication and leadership skills with experience in cross-functional collaboration to deliver impactful data solutions.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development