We are seeking a dynamic and self-motivated Senior Consultant - Full Stack Data Scientist to join our growing Data & Analytics team. This is an exciting opportunity for a seasoned professional to lead full lifecycle data science projects, contribute to business development, and mentor junior team members in a collaborative, fast-paced environment. As a Senior Consultant, you will wear many hats, taking ownership of projects from conception to deployment, while also supporting the growth of the team and helping clients navigate their data and analytics challenges.

This role is ideal for someone with a deep technical skill set, strong consulting background, and a passion for delivering impactful data-driven solutions. If you’re looking for a position where you can make a significant impact, contribute to strategic decisions, and grow professionally, we want to meet you!

Key Responsibilities:

End-to-End Project Delivery:

• Lead the full lifecycle of data science projects, from data collection, processing, model development, and deployment, to monitoring and optimization.

• Translate complex business requirements into actionable data solutions and insights.

• Build scalable machine learning models and implement them into production environments using cloud platforms (AWS, Azure, GCP).

• Ensure high-quality deliverables on time and within budget.

Business Development:

• Partner with the leadership team to identify new opportunities, scope projects, and contribute to client proposals and presentations.

• Build and maintain relationships with clients to understand their evolving data needs and provide innovative solutions.

• Help drive growth by contributing to thought leadership, white papers, or webinars in the data and analytics space.

Team Leadership & Development:

• Mentor and guide junior data scientists and consultants, fostering a collaborative and supportive team culture.

• Provide technical oversight and review deliverables from junior team members to ensure the highest quality.

• Help shape and develop internal processes and best practices for the data science function.

Consulting & Client Engagement:

• Lead client engagements, communicate findings, and present data-driven recommendations to senior stakeholders.

• Use a consultative approach to help clients understand how to leverage data and advanced analytics to drive business decisions.

• Manage multiple projects simultaneously, ensuring client satisfaction and addressing any concerns proactively.

Experience:

• 6+ years of experience in data science, with a strong focus on end-to-end delivery of machine learning solutions and full-stack capabilities (data engineering, machine learning, model deployment).

• Proven experience in consulting and client-facing roles is highly desirable.

Technical Skills:

• Proficiency in programming languages such as Python or R, and SQL.

• Experience with data engineering tools (e.g., Spark, Hadoop, Airflow) and cloud platforms (AWS, Azure, GCP).

• Expertise in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and production deployment (APIs, Docker, Kubernetes).

• Strong understanding of statistical analysis, predictive modeling, and data visualization tools (Tableau, Power BI).

Consulting Skills:

• Ability to manage stakeholder relationships, navigate complex client environments, and deliver clear, actionable insights.

• Excellent communication skills, both written and verbal, with experience presenting to senior executives.

• A track record of contributing to business development efforts or growing client relationships.

Soft Skills:

• Self-motivated with a passion for learning and growing in the data science space.

• A team player who thrives in a dynamic, collaborative, and fast-paced environment.

• Strong problem-solving skills, with the ability to think strategically and handle multiple projects concurrently.

Preferred Qualifications:

• Advanced degree (Master’s or PhD) in a quantitative field such as Data Science, Computer Science, Statistics, Engineering, or related field.

• Previous experience working in a consulting firm or a client-facing environment.

• Experience with MLOps, CI/CD pipelines, and model monitoring in production.

• Familiarity with agile methodologies and project management tools.