Principle Data Solutions Architect

at  Freemind Solutions

Project/ Task A key player in shaping our data science strategies and
driving innovative solutions. This role requires a seasoned
professional with a deep understanding of data science,
exceptional leadership skills, and the ability to architect and
deliver cutting-edge data-driven solutions. Join us to lead the
charge in transforming data into actionable insights and
driving business success through strategic technical
leadership.
Qualification  Advanced degree (Ph.D. or Master’s) 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.
Job Profile
(Brief description)
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.
years of Experience 15-20
Technology Data Bricks, Domino Data, Palantir AWS, Azure, GCP, Data
Modeling, Data Architecture, ML/AI/ LLM, SnowFlake,
OpenAI, LAMA3
Skill Set 1. 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).
2. 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).
3. 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.
4. Data Management & Storage:
 Knowledge of SQL and NoSQL databases (e.g.,
MySQL, PostgreSQL, MongoDB, Cassandra).
 Experience with data lakes and data warehouses.
5. 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
6. 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).
7. Integration & Interoperability:
 Experience in integrating various data sources and
systems.
 Knowledge of API design and integration patterns.
8. 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
9. Analytical Thinking:
 Strong problem-solving skills and the ability to analyze
complex datasets to derive actionable insights.
 Proficiency in statistical analysis and hypothesis
testing.
10. 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
11. 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.
12. 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 Type: Full-time
Pay: $120,997.70 - $140,395.08 per year
Work Location: On the roa

Please refer the Job description for details