Senior Data Scientist

8 Months ago • 4-8 Years • Data Analysis

Job Summary

Job Description

Senior Data Scientist needed with strong Probability Theory, Statistics, Machine Learning expertise. Proficiency in Python, SQL, and CRISP-ML(Q) required. Experience with banking transaction data and anti-money laundering systems preferred. This hybrid role offers a flexible work environment and opportunities for growth within a global company.
Must have:
  • Probability Theory
  • Machine Learning
  • Python Proficiency
  • SQL Proficiency
Good to have:
  • MLOps Experience
  • Deep Learning
  • Large Language Models
  • Databricks Experience
Perks:
  • Hybrid Work
  • Growth Opportunities

Job Details

About the job

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


About us:

India is a strategic growth market for Ciklum.

Be a part of a big story created right now. Let’s grow our delivery center in India together! Boost your skills and knowledge: create and innovate with like-minded professionals — all of that within a global company with a local spirit and start-up soul.

Supported by Recognize Partners and expanding globally, we will engineer the experiences of tomorrow!


Be bold, not bored!

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

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About The Company

Chennai, Tamil Nadu, India (Hybrid)

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