Description

As a Lead Data Scientist, you will be responsible for leading a team of data scientists and analysts to solve complex business problems using data-driven techniques. You will work closely with cross-functional teams to design, implement, and scale data science models and solutions. Your expertise will influence strategic decisions, drive innovation, and enable data-centric transformations across the organization.

Key Responsibilities:

  • Lead the development and deployment of advanced data science models and machine learning algorithms to address business challenges.
  • Manage and mentor a team of data scientists, providing guidance and fostering a collaborative environment that encourages innovation.
  • Collaborate with stakeholders from different departments (e.g., engineering, marketing, product, and leadership) to understand business needs and deliver actionable insights.
  • Drive the adoption of data science best practices, tools, and frameworks across the organization.
  • Oversee end-to-end data science workflows, including data collection, feature engineering, model selection, evaluation, and deployment.
  • Ensure the scalability and robustness of data science solutions in a production environment.
  • Utilize statistical analysis, machine learning, deep learning, and other advanced techniques to drive insights and business outcomes.
  • Communicate findings, insights, and recommendations to both technical and non-technical stakeholders through reports, presentations, and dashboards.
  • Stay updated with the latest trends in data science and AI, exploring new technologies and methodologies that can enhance the organization’s capabilities.

Qualifications:

  • Master’s or Ph.D. in Computer Science, Mathematics, Statistics, Engineering, or a related field.
  • 10+ years of experience in data science, machine learning, and analytics, with a proven track record of leading teams and delivering impactful solutions.
  • Strong proficiency in programming languages such as Python, R, SQL, and other data science and machine learning libraries (e.g., TensorFlow, scikit-learn, PyTorch).
  • Extensive experience with machine learning algorithms, statistical modeling, and data mining techniques.
  • Proven experience in data wrangling, feature engineering, and working with large, complex datasets.
  • Deep understanding of big data technologies and platforms (e.g., Hadoop, Spark, AWS, GCP).
  • Solid experience with data visualization tools (e.g., Tableau, Power BI) and techniques to communicate complex insights effectively.
  • Strong knowledge of data architectures, cloud infrastructure, and best practices for deploying data science models at scale.
  • Excellent leadership, communication, and project management skills.
  • Strong business acumen and ability to translate business problems into data science solutions.

Preferred Skills:

  • Experience in deploying and maintaining machine learning models in production environments.
  • Familiarity with deep learning, natural language processing (NLP), or reinforcement learning.
  • Knowledge of Agile methodologies and working in cross-functional teams.
  • Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization (e.g., Docker, Kubernetes)

Education

Any Graduate