Senior Data Scientist

Recro; Mumbai; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Recro is seeking an experienced Data Scientist to lead initiatives in Machine Learning, AI, and GenAI. The role involves end-to-end project ownership, where you will design scalable solutions and ensure business adoption.

The ideal candidate will have 5–6 years of experience in Data Science, with strong programming skills in Python and SQL, and a proven track record in machine learning and generative AI. Excellent communication skills for stakeholder management are essential.

Qualifications

• 5–6 years of relevant experience in Data Science, Machine Learning, and AI/GenAI solution development.
• Strong analytical thinking with the ability to break down complex problems.
• Excellent communication and storytelling skills for both technical and non-technical stakeholders.

Responsibilities

• Lead data science initiatives from problem definition to business adoption.
• Design scalable, robust production-ready ML solutions.
• Build, validate, and optimize machine learning models.

Skills

Python programming

SQL

Machine Learning

Deep Learning

Generative AI

Cloud platforms (AWS)

Big data technologies (Spark)

Data management

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics

Job description

• Cross-Functional Collaboration: Partner with business, operations, pricing, and sales teams to identify and prioritize high-impact opportunities for ML, AI, and GenAI-driven solutions.
• End-to-End Project Ownership: Lead data science initiatives from problem definition and ideation through development, deployment, and business adoption, ensuring timely and high-quality delivery.
• Solution Architecture: Design scalable, robust, and production-ready ML and GenAI solutions aligned with business objectives, with a strong focus on measurable impact and ROI.
• Hands-On Model Development: Build, validate, and optimize machine learning and AI models using state-of-the-art techniques, ensuring adherence to best practices in model development and experimentation.
• Stakeholder Communication: Translate complex analytical outputs into clear, actionable insights and present recommendations effectively to senior stakeholders and leadership teams.
• Deployment & Integration: Collaborate with data engineering and platform teams to operationalize models and integrate AI solutions seamlessly into business workflows and systems.
• Performance Monitoring & Optimization: Establish monitoring frameworks to track model performance, ensure reliability, and drive continuous improvement through retraining and refinement.
• Mentorship & Team Leadership: Mentor and guide junior data scientists and analysts, fostering technical excellence, structured problem-solving, and a culture of continuous learning.

DESIRED CANDIDATE PROFILE:

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (BE/BTech/MSc/MTech/PhD), with 5–6 years of relevant experience in Data Science, Machine Learning, and AI/GenAI solution development.
• Technical Proficiency: Strong programming skills in Python and SQL, with hands-on experience in building end-to-end data science solutions. Familiarity with modern ML frameworks and libraries is expected.
• AI/ML & GenAI Expertise: Proven experience across Machine Learning, Deep Learning, and Generative AI, with a strong track record of translating business problems into scalable, real-world AI solutions.
• Cloud & Data Engineering Skills: Practical experience with cloud platforms (preferably AWS), along with exposure to big data technologies such as Spark. Working knowledge of scalable data pipelines and MLOps practices is a plus.
• Data Management & Databases: Strong understanding of structured and unstructured data, with hands-on experience in SQL and NoSQL databases, and efficient data processing and retrieval techniques.
• Analytical & Problem-Solving Skills: Strong analytical thinking with the ability to break down complex problems, apply structured approaches, and deliver innovative, data-driven solutions.
• Communication & Stakeholder Management: Excellent communication and storytelling skills, with the ability to translate complex technical concepts into clear business insights for both technical and non-technical stakeholders.