Senior Associate Data Scientist

About ProArch:

At ProArch, we partner with businesses around the world to turn big ideas into better outcomes through IT services that span cybersecurity, cloud, data, AI, and app development. We’re 400+ team members strong across 3 countries (we call ourselves ProArchians)—and here’s what connects us all:

• A love for solving real business problems
• A belief in doing what’s right

What’s it like to work here?

• You’ll keep growing. You’ll work alongside domain experts who love to share what they know.
• You’ll be supported, heard, and trusted to make an impact.
• You’ll take on projects that touch industries, communities, and lives.
• You’ll have the time to focus on what matters most in your life outside of work.

At ProArch, you’ll be part of teams that design and deliver technology solutions solving real business challenges for our clients. With services spanning AI, Data, Application Development, Cybersecurity, Cloud & Infrastructure, and Industry Solutions, your work may involve building intelligent applications, securing business‑critical systems, or supporting cloud migrations and infrastructure modernization. 

Every role here contributes to shaping outcomes for global clients and driving meaningful impact. You’ll collaborate with experts across data, AI, engineering, cloud, cybersecurity, and infrastructure—solving complex problems with creativity, precision, and purpose. You’ll join a culture rooted in technology, curiosity, and continuous learning. A place where we move fast, trust you to make an impact, encourage innovation, and support your growth.

Job Description:

We are seeking an experienced and highly skilled Senior Associate Data Scientist to lead the design, development, and delivery of advanced analytics and machine learning solutions that drive strategic business outcomes. This role requires deep expertise in data science, predictive modeling, statistical analysis, and enterprise-scale AI/ML implementations, along with the ability to engage effectively with both technical and executive stakeholders.

The ideal candidate will possess a strong combination of technical excellence, consulting capabilities, and business acumen, enabling them to translate complex analytical challenges into impactful business solutions. The role involves collaborating with cross-functional teams, influencing key stakeholders, and delivering production-grade data science solutions that support organizational growth and innovation.

Key Responsibilities:
Data Science & Advanced Analytics Leadership

• Design, develop, and deploy advanced analytics, machine learning, and predictive modeling solutions to solve complex business challenges.
• Lead the development of forecasting, classification, regression, clustering, and optimization models.
• Apply statistical techniques and analytical methodologies to uncover actionable insights from structured and unstructured data.
• Drive the adoption of best practices in data science, machine learning, and model governance.

Machine Learning Solution Development:

• Build, train, evaluate, and deploy machine learning models using industry-standard frameworks and tools.
• Develop scalable and production-ready ML solutions that meet enterprise performance, reliability, and governance requirements.
• Implement model monitoring, validation, retraining, and performance optimization strategies.
• Ensure analytical models align with business objectives and deliver measurable value.

Azure Synapse Analytics & Data Platform Solutions:

• Design and develop end-to-end analytical solutions leveraging Azure Synapse Analytics.
• Build and optimize data pipelines, data transformations, and integrated analytics workflows.
• Collaborate with data engineering teams to ensure efficient data ingestion, preparation, and accessibility.
• Support enterprise analytics initiatives through scalable cloud-based data architectures.

Stakeholder Engagement & Consulting:

• Partner with business leaders, product teams, architects, and engineering teams to identify opportunities for data-driven decision-making.
• Translate complex analytical findings into clear business recommendations and actionable insights.
• Communicate effectively with stakeholders across all organizational levels, including senior leadership and C-suite executives.
• Serve as a trusted advisor on data science strategy, analytics adoption, and AI-driven transformation initiatives.

Solution Design & Business Requirements:

• Lead discovery workshops, requirements-gathering sessions, and solution design discussions.
• Define analytical approaches, success metrics, and implementation roadmaps aligned with business goals.
• Evaluate solution feasibility, risks, and expected business outcomes.
• Collaborate with cross-functional teams to ensure successful project execution and delivery.

Innovation & Continous Improvement:

• Stay current with emerging trends, technologies, and methodologies in Data Science, Artificial Intelligence, and Machine Learning.
• Identify opportunities to improve analytical processes, automation, and model effectiveness.
• Contribute to the organization's analytics strategy and innovation roadmap.
• Promote a culture of continuous learning, experimentation, and data-driven decision-making.

Leadership & Mentorship:

• Provide technical leadership and guidance to data scientists, analysts, and project teams.
• Review model design, implementation approaches, and analytical outputs to ensure quality and consistency.
• Support capability development through coaching, mentoring, and knowledge sharing.

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field.
• 10–15 years of experience in Data Science, Machine Learning, Advanced Analytics, or related disciplines.
• Strong expertise in predictive modeling, forecasting, classification, regression, and statistical analysis.
• Extensive experience developing and deploying enterprise-grade machine learning solutions.
• Hands-on experience with Azure Synapse Analytics, including data pipelines, analytical models, and integrated analytics solutions.
• Advanced programming proficiency in Python and SQL.
• Experience with machine learning frameworks and libraries such as:
• Scikit-Learn
• XGBoost
• TensorFlow
• PyTorch
• Similar ML frameworks
• Strong knowledge of model evaluation, experimentation methodologies, feature engineering, and performance optimization.
• Experience working with large-scale structured and unstructured datasets.
• Proven experience delivering production-grade data science solutions within enterprise environments.

Preferred Qualifications

• Experience working in cloud-based analytics environments, particularly Microsoft Azure.
• Exposure to MLOps, model deployment automation, and model lifecycle management.
• Experience leading enterprise AI and digital transformation initiatives.
• Knowledge of data governance, responsible AI practices, and model risk management.
• Experience working in consulting, professional services, or customer-facing environments.

Key Competencies

Technical Competencies

• Advanced Data Science and Machine Learning expertise.
• Statistical modeling and experimental design.
• Predictive analytics and forecasting.
• Azure Synapse Analytics and cloud-based analytics platforms.
• Data engineering and analytical solution architecture.
• Model deployment, monitoring, and optimization.

Business & Consulting Competencies

• Strong analytical and problem-solving capabilities.
• Excellent stakeholder management and relationship-building skills.
• Ability to influence decision-making through data-driven insights.
• Strong commercial awareness and business acumen.
• Ability to align analytical solutions with organizational objectives.
• Experience managing complex technical initiatives independently.

Communication & Leadership Competencies

• Outstanding communication, presentation, and consulting skills.
• Executive-level storytelling and data visualization capabilities.
• Ability to communicate complex technical concepts to non-technical audiences.
• Confidence presenting recommendations and insights to senior leadership and C-suite stakeholders.
• Strong facilitation skills for workshops, strategy discussions, and executive engagements.

Success Profile

The successful candidate will demonstrate:

• Deep technical expertise combined with strong business understanding.
• Exceptional stakeholder engagement and executive communication skills.
• A strategic mindset focused on delivering measurable business value.
• The ability to lead complex analytics initiatives from concept through production deployment.
• A passion for innovation, continuous improvement, and data-driven transformation.

Impact of the Role

This role directly contributes to:

• Accelerating data-driven decision-making across the organization.
• Delivering scalable AI and Machine Learning solutions that generate business value.
• Enhancing enterprise analytics capabilities and innovation.
• Strengthening stakeholder confidence through actionable insights and strategic recommendations.
• Driving digital transformation through advanced analytics and intelligent automation.