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Purchase Order Data Scientist in Kenya Nairobi –Free Word Template Download with AI

Professional Services Procurement — Data Scientist Engagement Issued in Kenya Nairobi, Republic of Kenya Purchase Order Number PO-KN-2025-DS-0472 Date of Issue 14 June 2025 Delivery Location Kenya Nairobi, Westlands Business District Valid Until 14 July 2025 1. Purchasing Entity (Buyer)
Company Name: Savanna Analytics & Intelligence Ltd. Registration No.: KE-RC-2019-88432
Address: 4th Floor, River Road Towers, Westlands, Kenya Nairobi Tax ID (KRA PIN): P051234567X
Contact Person: Mr. James Mwangi, Head of Procurement Email: [email protected]
Phone: +254 722 555 0198 Bank: Equity Bank, A/C 0123456789
2. Supplier / Service Provider (Seller)
Consultant Name: Dr. Amina Otieno, Senior Data Scientist Professional ID: KICP-DS-2021-0034
Address: 12 Kimathi Street, Kilimani, Kenya Nairobi Tax ID (KRA PIN): P098765432Y
Email: [email protected] Phone: +254 733 444 2210
3. Scope of Work & Line Items

This Purchase Order is issued to formally engage a qualified Data Scientist to deliver advanced analytics, machine learning model development, and predictive data solutions for Savanna Analytics & Intelligence Ltd. The Data Scientist shall perform all professional duties from the designated office located in Kenya Nairobi, ensuring full compliance with local data protection regulations under the Kenya Data Protection Act, 2019.

Item No. Description of Service Duration Rate (KES) Amount (KES)
1 End-to-end Data Science project: customer churn prediction model development using Python, scikit-learn, and TensorFlow. The Data Scientist shall conduct exploratory data analysis, feature engineering, model training, validation, and deployment. 8 weeks 185,000 / week 1,480,000
2 Development of a real-time data pipeline for processing transactional data streams. The Data Scientist shall design, build, and document the pipeline using Apache Kafka and Spark, hosted on the company's cloud infrastructure in Kenya Nairobi. 4 weeks 185,000 / week 740,000
3 Training and knowledge transfer sessions for the internal analytics team (up to 12 staff members) on advanced machine learning techniques, statistical modelling, and data storytelling. Sessions to be conducted at the Kenya Nairobi office. 2 weeks 120,000 / week 240,000
4 Preparation of a comprehensive Data Science strategy roadmap for the fiscal year 2025/2026, including technology stack recommendations, budget projections, and talent acquisition plan for the Kenya Nairobi operations. 2 weeks 150,000 / week 300,000
TOTAL CONTRACT VALUE (KES) 2,760,000
VAT @ 16% (KES) 441,600
GRAND TOTAL (KES) 3,201,600
4. Payment Terms
  • Payment shall be made in three (3) equal instalments via bank transfer to the supplier's designated account, subject to satisfactory milestone delivery as confirmed in writing by the Head of Procurement.
  • First instalment (33.33%): Due upon commencement of the Data Scientist engagement in Kenya Nairobi.
  • Second instalment (33.33%): Due upon completion of the machine learning model and data pipeline deliverables.
  • Third instalment (33.34%): Due upon final acceptance of the strategy roadmap and completion of all training sessions.
  • All payments are subject to a 30-day credit period from the date of invoice receipt. Late payments shall attract interest at 2% per month as stipulated under Kenyan commercial law.
  • The supplier must issue a valid KRA-compliant invoice for each payment tranche. This Purchase Order does not constitute a guarantee of payment beyond the stated terms.
5. Terms and Conditions
  • This Purchase Order is governed by the laws of the Republic of Kenya. Any disputes arising from this engagement shall be resolved through arbitration in Kenya Nairobi in accordance with the Arbitration Act, 1995.
  • The Data Scientist shall maintain strict confidentiality of all proprietary data, algorithms, and business intelligence accessed during the course of this engagement. A separate Non-Disclosure Agreement (NDA) is attached hereto as Annex A.
  • All intellectual property, models, code, and documentation produced under this Purchase Order shall be the sole property of Savanna Analytics & Intelligence Ltd. upon full payment.
  • The Data Scientist is engaged as an independent contractor and not as an employee. The supplier is responsible for their own income tax, National Social Security Fund (NSSF), and any other statutory deductions applicable in Kenya Nairobi.
  • The supplier shall comply with all applicable Kenyan data protection and privacy regulations, including the Kenya Data Protection Act, 2019, and guidelines issued by the Office of the Data Protection Commissioner.
  • This Purchase Order may be amended only by mutual written agreement signed by both parties. No verbal modifications shall be binding.
  • The supplier shall provide a minimum of 14 days' written notice in the event of inability to perform the contracted Data Scientist duties. Failure to do so shall entitle the buyer to claim liquidated damages at 5% of the remaining contract value per week of delay.
  • All work deliverables must be submitted in digital format to the designated project manager at the Kenya Nairobi office no later than the agreed milestone dates.
6. Acceptance and Authorization

By signing below, both parties acknowledge and agree to the terms set forth in this Purchase Order for the engagement of the Data Scientist in Kenya Nairobi. This document constitutes a binding commercial agreement upon execution by both authorized representatives.

For and on behalf of Savanna Analytics & Intelligence Ltd.
Name: James Mwangi
Title: Head of Procurement
Signature: _________________________
Date: _________________________
For and on behalf of the Data Scientist (Supplier)
Name: Dr. Amina Otieno
Title: Senior Data Scientist
Signature: _________________________
Date: _________________________

This Purchase Order (PO-KN-2025-DS-0472) was prepared and issued in Kenya Nairobi, Republic of Kenya. It is valid for a period of thirty (30) calendar days from the date of issue. For queries, contact the Procurement Department at [email protected] or +254 722 555 0198. This document is confidential and intended solely for the named parties.

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