Data Scientist – Generative AI

Job Summary:
We are seeking a talented Data Scientist with expertise in Generative AI and Agentic AI to join our team. You will lead and drive AI/data science projects independently, from data collection to model deployment. Your role will significantly contribute to business objectives by implementing scalable AI solutions that deliver actionable insights and drive innovation across the organization.

Software Requirements:

• Required Proficiency:

  • Python, R, Spark, Teradata SQL, SAS for data analysis and modeling
  • Experience with Big Data Platforms such as Hadoop/HDFS, Omnia, Hive, and Spark
  • AWS cloud experience

• Preferred Proficiency:

  • Familiarity with H2O.ai, GitHub, and ML Engineering tools

Overall Responsibilities:

• Lead AI/data science projects independently, owning the end-to-end process from data collection to model deployment.
• Apply Gen AI, NLP, Computer Vision, Deep Learning, advanced statistical, and ML predictive modeling techniques.
• Collaborate with business and cross-functional teams to understand needs and implement AI-driven solutions.
• Present complex results to non-technical stakeholders, translating data insights into actionable business strategies.
• Develop and deploy production-grade AI/machine learning models in cloud-based and on-prem platforms.
• Drive innovation by exploring new approaches for solving complex business problems through data analysis and AI/ML modeling.
• Contribute to the strategic planning and direction of AI/data science initiatives.

Technical Skills (By Category):

• Programming Languages:

  • Required: Python, R
  • Preferred: Spark, Teradata SQL, SAS

• Databases/Data Management:

  • Required: Hive, Spark
  • Preferred: Teradata, Omnia

• Cloud Technologies:

  • Required: AWS
  • Preferred: Additional cloud platforms

• Frameworks and Libraries:

  • Required: NLP, Computer Vision, Deep Learning

• Development Tools and Methodologies:

  • Required: GitHub, ML Engineering

Experience Requirements:

• 7–15 years of experience in data science or statistical modeling, preferably within retail banking or financial services.
• Experience in risk or audit domains is beneficial.

Day-to-Day Activities:

• Engage in problem formulation and suggest AI solutions for maximum business impact.
• Lead cross-functional teams in the design and execution of AI/data science projects.
• Stay abreast of emerging technologies and industry trends.
• Support the adoption of AI/data science across the organization.

Qualifications:

• Required: Bachelor’s or Master’s degree in Mathematics, Statistics, Economics, Econometrics, Computer Science, or Engineering.
• Commitment to continuous professional development through industry certifications and training.

Professional Competencies:

• Strong critical thinking and problem-solving capabilities.
• Leadership and teamwork abilities.
• Excellent communication and stakeholder management skills.
• Adaptability and learning orientation.
• Innovation mindset blended with pragmatic thinking.
• Effective time and priority management skills.

S​YNECHRON’S DIVERSITY & INCLUSION STATEMENT
 

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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