
About the Role
We are looking for an analytical and detail-oriented Data Scientist with deep expertise in graph analytics, network analysis, and scalable data engineering. This is not a conventional machine learning role — the focus is on understanding complex relationships, structures, and patterns within large-scale datasets using graph-based methods and statistical modeling. You will work in a collaborative, fast-paced environment and be expected to contribute across the full data lifecycle — from raw data exploration through to production-grade analytical systems.
This is a full-time, in-office role based out of our Pune office (5 days a week).
Key Responsibilities
Graph Analytics & Network Analysis
• Design and implement graph-based models to identify patterns, clusters, communities, and relationships within complex datasets.
• Apply network analysis techniques using metrics such as clustering coefficient, degree assortativity, density, Gini index, and small-world index.
• Perform multi-hop network traversals and community detection using algorithms such as Louvain partitioning and similar graph clustering approaches.
• Build and query graph databases (Neo4j, ArangoDB) using Cypher Query Language to extract structural insights from connected data.
• Leverage GPU-accelerated graph libraries (cuGraph) to scale graph computations across large datasets efficiently.
Data Engineering & Pipeline Development
• Conduct thorough Exploratory Data Analysis (EDA) on large-scale structured and semi-structured datasets to surface quality issues, distributions, and key features.
• Build, optimize, and maintain scalable data pipelines and stored procedures across cloud data platforms such as BigQuery, PostgreSQL, or Hive.
• Automate data workflows using orchestration tools such as Apache Airflow or Kubeflow Pipelines.
• Apply GPU-accelerated computing (CUDA, CuPy, cuDF) to optimize processing performance on high-volume data workloads.
• Ensure data integrity, reproducibility, and documentation across all analytical workflows.
Statistical Modeling & Insight Generation
• Apply statistical modeling techniques to detect behavioral anomalies, trends, and patterns within datasets.
• Use time series analysis to identify temporal patterns and changes in data over time.
• Translate analytical findings into clear, actionable insights for both technical and non-technical stakeholders.
• Build dashboards and reports using visualization tools (e.g., Trino Superset) to communicate results effectively.
Collaboration & Documentation
• Work closely with product, engineering, and business teams to understand requirements and deliver relevant analytical solutions.
• Contribute to internal knowledge sharing through workshops, documentation, and peer reviews.
• Maintain well-documented codebases and analytical frameworks for long-term maintainability.
Required Skills & Qualifications
Must-Have
• 3+ years of experience in a Data Science, Data Analytics, or Graph Analytics role.
• Strong proficiency in Python with hands-on experience using NumPy, Pandas, CuPy, and cuDF.
• Practical experience with graph analytics libraries — NetworkX, cuGraph, Neo4j, or ArangoDB.
• Solid understanding of graph theory concepts: community detection, network metrics, graph traversal, and clustering algorithms.
• Proficiency in SQL; experience with BigQuery, PostgreSQL, MS SQL, Hive, or similar databases.
• Experience with GPU-based computing using CUDA for performance-critical data tasks.
• Strong analytical thinking and ability to work independently on ambiguous, open-ended problems.
Good to Have
• Experience with Cypher Query Language for querying graph databases (Neo4j / ArangoDB).
• Familiarity with graph ML frameworks such as PyTorch Geometric.
• Exposure to workflow orchestration tools — Apache Airflow or Kubeflow Pipelines.
• Knowledge of cloud data tools such as Trino, MinIO, or IBM Datastage.
• Basic scripting skills in Bash or C++ for automation or performance tasks.
• Experience presenting data insights to senior stakeholders or cross-functional teams.
• Research publications, patents, or open-source contributions in graph analytics or data science are a strong plus.
What We Offer
• Opportunity to solve high-impact, large-scale data problems using modern graph and analytics tools.
• Exposure to cutting-edge technologies including GPU-accelerated computing and graph ML.
• Collaborative, intellectually stimulating work environment with a strong engineering culture.
• Competitive compensation with performance-based incentives.
• Learning & development support — certifications, courses, and conference participation.
• Centrally located Pune office with a structured, in-person team culture.

About Wissen Technology
About
The Wissen Group was founded in the year 2000. Wissen Technology, a part of Wissen Group, was established in the year 2015. Wissen Technology is a specialized technology company that delivers high-end consulting for organizations in the Banking & Finance, Telecom, and Healthcare domains.
With offices in US, India, UK, Australia, Mexico, and Canada, we offer an array of services including Application Development, Artificial Intelligence & Machine Learning, Big Data & Analytics, Visualization & Business Intelligence, Robotic Process Automation, Cloud, Mobility, Agile & DevOps, Quality Assurance & Test Automation.
Leveraging our multi-site operations in the USA and India and availability of world-class infrastructure, we offer a combination of on-site, off-site and offshore service models. Our technical competencies, proactive management approach, proven methodologies, committed support and the ability to quickly react to urgent needs make us a valued partner for any kind of Digital Enablement Services, Managed Services, or Business Services.
We believe that the technology and thought leadership that we command in the industry is the direct result of the kind of people we have been able to attract, to form this organization (you are one of them!).
Our workforce consists of 1000+ highly skilled professionals, with leadership and senior management executives who have graduated from Ivy League Universities like MIT, Wharton, IITs, IIMs, and BITS and with rich work experience in some of the biggest companies in the world.
Wissen Technology has been certified as a Great Place to Work®. The technology and thought leadership that the company commands in the industry is the direct result of the kind of people Wissen has been able to attract. Wissen is committed to providing them the best possible opportunities and careers, which extends to providing the best possible experience and value to our clients.
Connect with the team
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