Senior Data Scientist

Description

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

• Development of prototype solutions, mathematical models, algorithms, machine learning techniques, and robust analytics to support analytic insights and visualization of complex data sets
• Work on exploratory data analysis so you can navigate a dataset and come out with broad conclusions based on initial appraisals
• Provide optimization recommendations that drive KPIs established by product, marketing, operations, PR teams, and others
• Interacts with engineering teams and ensures that solutions meet customer requirements in terms of functionality, performance, availability, scalability, and reliability
• Work directly with business analysts and data engineers to understand and support their use cases
• Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions
• Drive innovation by exploring new experimentation methods and statistical techniques that could sharpen or speed up our product decision-making processes
• Cross-train other team members on technologies being developed, while also continuously learning new technologies from other team members
• Contribute to the Unit activities and community building, participate in conferences, and provide excellence in exercise and best practices
• Support marketing & sales activities, customer meetings and digital services through direct support for sales opportunities & providing thought leadership & content creation for the service

Requirements

We know that sometimes, you can t tick every box. We would still love to hear from you if you think you re a good fit!

• BSc, MSc, or PhD in Mathematics, Statistics, Computer Science, Engineering, Operations Research, Econometrics, or related fields
• Strong knowledge of Probability Theory, Statistics, and a deep understanding of the Mathematics behind Machine Learning
• Proficiency with CRISP-ML(Q) or TDSP methodologies for addressing commercial problems through data science solutions
• Hands-on experience with various machine learning techniques, including but not limited to:
  • Regression
  • Classification
  • Clustering
  • Dimensionality reduction
• Proficiency in Python for developing machine learning models and conducting statistical analyses
• Strong understanding of data visualization tools and techniques (e. g. , Python libraries such as Matplotlib, Seaborn, Plotly, etc. ) and the ability to present data effectively

Specific technical requirements:

• Proficiency in SQL for data processing, data manipulation, sampling, and reporting
• Experience working with imbalanced datasets and applying appropriate techniques
• Experience with time series data, including preprocessing, feature engineering, and forecasting
• Experience with outlier detection and anomaly detection
• Experience working with various data types: text, image, and video data
• Familiarity with AI/ML cloud implementations (AWS, Azure, GCP) and cloud-based AI/ML services (e. g. , Amazon SageMaker, Azure ML)

Domain experience:

• Strong experience working with transaction data from banking systems (e. g. , payments, deposits, loans) and understanding of core banking systems
• Expertise in analyzing customer behavior patterns, including segmentation, lifetime value (CLTV), and customer journey mapping
• Knowledge of Anti-Money Laundering transaction monitoring systems and techniques such as anomaly detection to spot unusual activities that could indicate money laundering
• Familiarity with KYC procedures and the use of data science to enhance identity verification and improve the customer onboarding process
• Expertise in building models to predict customer default risk, non-payment probability, and loss given default using advanced machine learning techniques
• Experience in developing machine learning models for fraud detection, including real-time scoring, anomaly detection, and the use of graph analytics for network-based fraud schemes
• Experience with algorithmic trading models, high-frequency trading, portfolio optimization, and quantitative finance for investment banking or wealth management
• Familiarity with building stress testing models that simulate adverse market conditions to assess the bank s resilience under stress scenarios
• Expertise in identifying causal relationships between financial variables, such as changes in interest rates and loan demand or credit risk, using causal inference methods
• Knowledge of data privacy laws and frameworks such as GDPR, CCPA, and local banking data privacy regulations to ensure that financial data is handled securely and in compliance
• Expertise in managing sensitive financial data in a secure and compliant manner, including encryption and tokenization to protect personally identifiable information (PII) and transaction records
• Understanding of banking regulations and frameworks such as Basel III, IFRS 9, CCAR, and AML (Anti-Money Laundering) to ensure compliance in modeling and reporting
• Experience with financial data platforms such as Bloomberg Terminal, Refinitiv, or banking data warehouses, and knowledge of open banking APIs
• Ability to work with finance, risk, compliance, and technology teams to align data science solutions with business objectives and regulatory requirements

Good to have skills:

• Experience with MLOps, including integration of machine learning pipelines into production environments, Docker, and containerization/orchestration (e. g. , Kubernetes)
• Experience in deep learning development using TensorFlow or PyTorch libraries
• Experience with Large Language Models (LLMs) and Generative AI applications
• Advanced SQL proficiency, with experience in MS SQL Server or PostgreSQL
• Familiarity with platforms like Databricks and Snowflake for data engineering and analytics
• Experience working with Big Data technologies (e. g. , Hadoop, Apache Spark)
• Familiarity with NoSQL databases (e. g. , columnar or graph databases like Cassandra, Neo4j)

Business-related requirements:

• Proven experience in developing data science solutions that drive measurable business impact, with a strong track record of end-to-end project execution
• Ability to effectively translate business problems into data science problems and create solutions from scratch using machine learning and statistical methods
• Excellent project management and time management skills, with the ability to manage complex, detailed work and effectively communicate progress and results to stakeholders at all levels

Desirable

• Research experience with peer-reviewed publications
• Recognized achievements in data science competitions, such as Kaggle
• Certifications in cloud-based machine learning services (AWS, Azure, GCP)

What's in it for you

• Care: your mental and physical health is our priority. We ensure comprehensive company-paid medical insurance, as well as financial and legal consultation
• Tailored education path: boost your skills and knowledge with our regular internal events (meetups, conferences, workshops), Udemy licence, language courses and company-paid certifications
• Growth environment: share your experience and level up your expertise with a community of skilled professionals, locally and globally
• Flexibility: hybrid work mode at Chennai or Pune
• Opportunities: we value our specialists and always find the best options for them. Our Resourcing Team helps change a project if needed to help you grow, excel professionally and fulfil your potential
• Global impact: work on large-scale projects that redefine industries with international and fast-growing clients
• Welcoming environment: feel empowered with a friendly team, open-door policy, informal atmosphere within the company and regular team-building events