Company Description
AKSHIKA Group is a leading business advisory firm dedicated to providing exceptional client experiences through primary research, risk management, System implementation, and investment decision-making platforms. We offer comprehensive advisory and consulting services globally.
R0001. Lead Data Engineers:
Role Description
Owns the end-to-end data architecture, leads the data engineering team, and ensures reliable, scalable data platforms that power analytics, AI, and reporting across the organization.
Key Responsibilities
- Design, build, and maintain scalable batch/streaming data pipelines (ETL/ELT) on cloud data platforms (e.g., Snowflake, Databricks, BigQuery).
- Define and own data architecture, modeling standards, and best practices for ingestion, transformation, and serving.
- Lead and mentor data engineers; perform code reviews and ensure engineering excellence and documentation.
- Implement robust data quality, observability, lineage, and governance controls.
- Partner with Data Science, Product, Risk, and Finance to translate business needs into data solutions and self-service layers.
- Evaluate and introduce new data technologies, frameworks, and patterns to improve performance, reliability, and cost.
- Ensure security, privacy, and compliance (PII, GDPR/DPDP, SOC2) within data platforms.
R0002. Data Scientist
Role Description
Develops data-driven insights, models, and experiments to solve complex business problems, improve decision-making, and power AI/ML features in products and internal tools.
Key Responsibilities
- Frame analytical and ML problems from ambiguous business questions; define hypotheses, metrics, and success criteria.
- Explore, clean, and transform large, complex datasets; perform EDA and feature engineering with modern tooling.
- Build, validate, and deploy ML models (classification, regression, time-series, NLP, recommendation) into production workflows.
- Design and analyze A/B tests and experiments; communicate results and trade-offs to non-technical stakeholders.
- Create clear visualizations, dashboards, and narratives that translate complex analysis into actionable recommendations.
- Collaborate with Data Engineering to ensure robust data foundations and with Product/Engineering to operationalize models.
- Monitor model performance, data drift, and bias; iterate models over time to maintain business impact.
R0003. Climate Risk Implementation Consultants (3)
Role Description
Implements climate and environmental risk solutions for financial institutions and corporates, translating regulatory and methodological frameworks into practical data, modeling, and reporting workflows
Key Responsibilities
- Lead end-to-end implementation of climate risk platforms (physical & transition risk) for banking, insurance, and corporate clients.
- Translate regulatory, supervisory, and voluntary frameworks (e.g., NGFS, TCFD, ISSB, ECB/BoE expectations) into data, modeling, and reporting requirements.
- Work with client risk, finance, and sustainability teams to design target-state data models, scenarios, and stress-testing methodologies.
- Configure and validate climate risk engines (PD/LGD overlays, sector pathways, exposure mapping) and reporting templates.
- Coordinate with internal Product and Engineering teams to refine features based on client feedback and emerging regulations.
- Prepare high-quality client artefacts (BRDs, configuration docs, test plans, UAT scripts, training materials).
- Support pre-sales (demos, RFP responses) and thought leadership (client workshops, POVs, whitepapers).
R0004. Legal-Tech Implementation Consultants
Role Description
Bridges legal, operations, and technology teams to implement contract lifecycle management (CLM), legal AI, and related legal‑tech platforms, ensuring adoption and measurable value for in‑house legal and business users.
Key Responsibilities
- Lead discovery and requirements workshops with Legal, Sales, Procurement, and Compliance to map current vs target-state legal workflows.
- Configure legal‑tech platforms (CLM, contract review AI, knowledge management, e‑billing) including templates, clause libraries, workflows, and integrations.
- Design data and document migration strategies; oversee cleansing, mapping, and validation of legacy contracts and matters.
- Define and implement approval flows, playbooks, negotiation guardrails, and reporting (cycle times, risk flags, policy adherence).
- Coordinate with client IT for SSO, DMS/CRM/ERP integrations (e.g., M365, Salesforce, SAP) and security reviews.
- Run UAT, train end‑users (lawyers, contract managers, business stakeholders), and establish change‑management and adoption KPIs.
- Provide post‑go‑live hypercare, optimization, and ongoing best‑practice advisory.
R0005. Senior Advisors (AI & ML)
Role Description
Acts as a strategic advisor to executive leadership and product teams on AI/ML strategy, architecture, governance, and high‑impact use cases, ensuring safe, scalable value creation from advanced analytics and generative/agentic AI.
Key Responsibilities
- Define AI/ML strategy and roadmap aligned with business objectives, including prioritization of high‑ROI use cases across functions.
- Advise on AI architecture choices (data platforms, MLOps, LLM/RAG stacks, agentic frameworks) and vendor/partner selection.
- Establish AI governance: model risk management, explainability, fairness, privacy, and compliance with evolving regulations.
- Review and challenge key models and initiatives (credit risk, fraud, pricing, personalization, operations optimization, gen‑AI copilots).
- Mentor data science and engineering leaders; raise bar on technical quality, experimentation, and documentation.
- Engage with C‑suite and boards to communicate AI opportunities, risks, and investment cases in clear, non‑technical language.
- Represent the organization in external forums (clients, regulators, conferences) and contribute to thought leadership.