Solution Architech @ Criticalriver

Role: Solution Architect

Years of Experience: 15 years to 20 years.

Location: Hyderabad

Job Profile

Principal Data Science Solution Architect and be a driving force in shaping the future of data-driven innovation. A strategic thinker with a passion for turning complex challenges into transformative solutions.

Technology Data Bricks, Domino Data, Palantir AWS, Azure, GCP, Data Modelling, Data Architecture, ML/AI/LLM, SnowFlake, OpenAI, LAMA3

Data Science & Machine Learning:

• Proficiency in machine learning algorithms and techniques (supervised, unsupervised, reinforcement learning).


• Experience with data preprocessing, feature engineering, and model evaluation.


• Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch).

Programming & Software Development:

• Strong coding skills in languages such as Python, R, Java, or Scala. Experience with software development practices, including version control (Git), testing, and continuous integration/continuous deployment (CI/CD).

Big Data Technologies:

• Proficiency in big data frameworks and tools (e.g., Hadoop, Spark, Kafka).


• Experience with data warehousing solutions (e.g., Snowflake, Redshift) and distributed computing.

Data Management & Storage:

• Knowledge of SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra).


• Experience with data lakes and data warehouses.

Cloud Platforms:

• Proficiency in cloud services (e.g., AWS, Azure, Google Cloud) for deploying and managing data science solutions.


• Experience with cloud-based machine learning services (e.g., AWS SageMaker, Azure Machine Learning). Architectural Skills

System Architecture Design:

• Ability to design scalable, reliable, and secure architectures for data science solutions.


• Understanding of microservices architecture, RESTful APIs, and service-oriented architecture (SOA).

Integration & Interoperability:

• Experience in integrating various data sources and systems.


• Knowledge of API design and integration patterns

Data Pipeline & Workflow Management:

• Proficiency in designing and managing ETL/ELT processes. Experience with workflow orchestration tools (e.g., Apache Airflow, Luigi). Analytical & problem-solving skills.

Analytical Thinking:

• Strong problem-solving skills and the ability to analyze complex datasets to derive actionable insights. Proficiency in statistical analysis and hypothesis testing.

Business Acumen:

• Ability to understand business problems and translate them into data science solutions.


• Experience in collaborating with stakeholders to gather requirements and deliver solutions that meet business needs. Communication & Collaboration Skills

Effective Communication:

• Strong verbal and written communication skills


• to explain complex technical concepts to non-technical stakeholders.


• Experience in creating technical documentation and presenting findings.

Collaboration & Leadership :

• Ability to lead cross-functional teams and collaborate with data scientists, engineers, and business analysts.


• Experience in mentoring and guiding junior team members.

Job Description

1. Strategic Leadership:

• Collaborate with executive leadership to define and execute the data science strategy aligned with business objectives.


• Provide thought leadership in data science and analytics, influencing decision-making at the highest levels.Drive innovation by identifying and implementing emerging technologies and methodologies.

1. Solution Architecture:

• Architect end-to-end data science solutions, ensuring scalability, reliability, and adherence to best practices.


• Collaborate with cross-functional teams to define technical requirements and design robust data architectures. Lead the development and implementation of advanced analytics and machine learning models.

1. Team Management:

• Lead and mentor a team of data scientists and solution architects.


• Foster a collaborative and results-driven team culture, encouraging continuous learning and development.


• Provide guidance on complex technical challenges and drive excellence in project execution.

1. Client Collaboration:

• Collaborate with clients and internal stakeholders to understand business challenges and develop tailored data science solutions.


• Act as a trusted advisor, translating business needs into technical requirements and delivering high-impact solutions.


• Build and maintain strong client relationships, ensuring satisfaction and success.

1. Innovation and Research:

• Stay abreast of industry trends, emerging technologies, and best practices in data science.


• Lead research initiatives to explore and integrate new tools and methodologies.

Qualification:

• Advanced degree (Ph.D. or Masters) in Computer Science, Data Science, or a related field.


• Proven experience (minimum of 10 years) in data science, with a focus on solution architecture and leadership.


• Expertise in machine learning, statistical modeling, data engineering, data modeling, and data visualization.


• Strong programming skills in languages such as Python, R, or Scala.


• Experience with big data technologies and cloud platforms (e.g., AWS, Azure, GCP). Experience with AI/ML and cloud platforms (e.g., Data Bricks, Domino Data, Palantir AWS, Azure, GCP).


• Excellent leadership, communication, and stakeholder management skills.


• Demonstrated success in leading and delivering complex data science projects. Strong problem-solving and critical-thinking abilities.