Senior Data Scientist

Posted 4 Days Ago
Be an Early Applicant
Hiring Remotely in India
Remote
Senior level
Information Technology • Consulting
The Role
Lead cross-functional ML initiatives: choose modeling approaches, define business-linked evaluation metrics, validate with synthetic and real data, deliver MLOps-enabled models on AWS, ensure reproducibility, compliance, cost optimization, and incremental value within short agile release cycles.
Summary Generated by Built In

Ciklum is looking for a Senior Data Scientist to join our team full-time in India.

We are a custom product engineering company that supports both multinational organizations and scaling startups to solve their most complex business challenges. With a global team of over 4,000 highly skilled developers, consultants, analysts and product owners, we engineer technology that redefines industries and shapes the way people live.

About the role:

As a Senior Data Scientist, become a part of a cross-functional development team engineering experiences of tomorrow.

Responsibilities:

  • Apply evaluation-driven development practices across all modeling work: define success criteria before building, and validate against them throughout the lifecycle
  • Select the appropriate modeling approach for the problem at hand — statistical modeling, classical ML, optimization, simulation, or GenAI — based on data characteristics, interpretability needs, and business context, rather than defaulting to a single technique
  • Define evaluation metrics that map directly to business and process outcomes (e.g., cost savings, cycle-time reduction, forecast accuracy, decision quality), not just model-centric metrics (accuracy, F1, RMSE) in isolation
  • Use a combination of synthetic data, historical data, and real-world validation to test model performance, robustness, and edge-case behavior before and after deployment
  • Demonstrate and document measurable improvements in decisions, processes, or outcomes as a required part of every delivery — not an afterthought.
  • Own delivery of assigned workstreams within 45-day versioned agile release cycles, ensuring each release ships incremental, measurable value to stakeholders
  • Collaborate with product, engineering, and business stakeholders to translate business problems into well-scoped modeling and analytics initiatives
  • Maintain clear versioning, documentation, and change logs across release cycles to support traceability and reproducibility
  • Build and deliver AI/ML platform components and analytics products on AWS, applying MLOps practices (CI/CD for models, model registries, monitoring, automated retraining pipelines)
  • Contribute to cost management and performance optimization for data and ML workloads (compute sizing, storage tiering, pipeline efficiency)
  • Support synthetic data generation, offline experimentation (A/B testing, shadow deployments, backtesting), and controlled real-world validation of models before full rollout
  • Balance model performance against explainability, regulatory/compliance requirements, and infrastructure cost when selecting and tuning approaches
  • Partner with risk, compliance, and governance functions as needed to ensure models meet audit and explainability standards

Requirements:

  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or a related quantitative field
  • 5–8+ years of experience delivering data science, ML, or analytics solutions in production environments
  • Demonstrated experience across multiple modeling paradigms: statistical modeling, machine learning, optimization, simulation, and exposure to GenAI applications
  • Hands-on experience with AWS-based ML/data platforms (e.g., SageMaker, S3, Glue, Redshift, Lambda) and MLOps tooling
  • Practical experience with synthetic data generation techniques, offline experimentation frameworks, and controlled validation methodologies
  • Strong proficiency in Python/R/SQL and standard ML libraries
  • Experience working in agile delivery models with short, versioned release cycles
  • Ability to communicate technical trade-offs (performance vs. explainability vs. cost) to both technical and non-technical stakeholders

Desirable:

  • Experience with explainability frameworks (SHAP, LIME) and model risk/compliance documentation
  • Experience with GenAI/LLM-based solution design and evaluation
  • Familiarity with cost-monitoring tools for cloud ML workloads (e.g., AWS Cost Explorer, tagging strategies)

What’s in it for you?

  • Strong community: Work alongside top professionals in a friendly, open-door environment
  • Growth focus: Take on large-scale projects with a global impact and expand your expertise
  • Tailored learning: Boost your skills with internal events (meetups, conferences, workshops), Udemy access, language courses, and company-paid certifications
  • Endless opportunities: Explore diverse domains through internal mobility, finding the best fit to gain hands-on experience with cutting-edge technologies
  • Care: We’ve got you covered with company-paid medical insurance, mental health support, and financial & legal consultations

About us:

At Ciklum, we are always exploring innovations, empowering each other to achieve more, and engineering solutions that matter. With us, you’ll work with cutting-edge technologies, contribute to impactful projects, and be part of a One Team culture that values collaboration and progress.

India is a strategic innovation hub for Ciklum, with growing teams in Chennai and Pune leading advancements in EdgeTech, AR/VR, IoT, and beyond. Join us to collaborate on game-changing solutions and take your career to the next level.

Explore, empower, engineer with Ciklum!

Interested already? We would love to get to know you! Submit your application. We can’t wait to see you at Ciklum.

#LI-MA1

Skills Required

  • Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Engineering, or related quantitative field
  • 5-8+ years delivering data science, ML, or analytics solutions in production
  • Demonstrated experience across statistical modeling, machine learning, optimization, simulation, and exposure to GenAI
  • Hands-on experience with AWS ML/data platforms (SageMaker, S3, Glue, Redshift, Lambda) and MLOps tooling
  • Practical experience with synthetic data generation, offline experimentation frameworks, and controlled validation methodologies
  • Strong proficiency in Python, R, and SQL and standard ML libraries
  • Experience working in agile delivery models with short, versioned release cycles
  • Ability to communicate technical trade-offs (performance vs. explainability vs. cost) to technical and non-technical stakeholders
  • Experience with explainability frameworks (SHAP, LIME) and model risk/compliance documentation
  • Experience with GenAI/LLM-based solution design and evaluation
  • Familiarity with cost-monitoring tools for cloud ML workloads (e.g., AWS Cost Explorer, tagging strategies)
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The Company
HQ: London
2,995 Employees
Year Founded: 2002

What We Do

Ciklum is a global Digital Solutions Company for Fortune 500 and fast-growing organisations alike around the world. The company is headquartered in London and has software development centres and branch offices in the United States, Spain, Switzerland, Denmark, Israel, Poland, Ukraine, Czech Republic, Slovakia, Romania, UAE and Pakistan. Ciklum builds tailored digital solutions that leverage emerging technologies for such clients as Just Eat, Flixbus, Metro Markets, EFG International, Zurich Insurance, Lottoland and others. For more information about us visit www.ciklum.com

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